Loan officer reviewing a mortgage database recapture benchmark worksheet with funnel metrics
Short answer: A mortgage database recapture benchmark is a defined way to measure what happens when a reviewed segment of known borrower or partner records enters an approved follow-up workflow. The benchmark must name its denominator, cohort, channel, time period, exclusions, and attribution window. Without those definitions, a “recapture rate” can be misleading.
This page is a measurement model, not an industry average. It does not claim that a particular response, application, or closing rate is typical. Use it to create a baseline from your own reviewed records, approved channels, and documented outcomes.
What database recapture means
Database recapture is the process of organizing a known mortgage relationship database, identifying records that may merit a review, and running an approved follow-up program. It is not a guarantee that a borrower will refinance, apply, respond, or close.
Keep the concept separate from trigger leads. Database recapture concerns a known relationship database. Trigger-lead rules concern a different source and use of consumer report information. Do not use one term as a legal substitute for the other.
Define the denominator before reporting a rate
Metric
Definition
Evidence source
Total database
All records in the selected cohort before filtering.
CRM export and selection date.
Contactable records
Records with a valid approved contact method.
CRM fields and policy review.
Reviewable records
Records that pass internal eligibility and suppression rules.
Segment definition and review log.
Campaign reach
Records actually sent, called, or assigned for an approved workflow.
Campaign and activity log.
Unique response
A recorded response from a reached record during the defined window.
CRM activity and channel analytics.
Appointment rate
Appointments divided by campaign reach.
Calendar and CRM records.
Application rate
Applications started divided by campaign reach.
LOS and CRM records.
Close rate
Closed loans divided by the stated cohort or reached records.
LOS and finance records.
Suppression rate
Records excluded or removed because of opt-out, invalid data, duplicate status, or review outcome.
Suppression log.
A transparent benchmark worksheet
Worksheet field
Your value
Question to answer
Cohort name
[enter]
Which relationship group is being measured?
Selection date
[enter]
When was the cohort exported or defined?
Total records
[enter]
How many records entered the review?
Contactable records
[enter]
How many have a valid approved channel?
Reviewed records
[enter]
How many passed the review and suppression process?
Reached records
[enter]
How many actually entered the workflow?
Unique responses
[enter]
What counts as a response?
Appointments
[enter]
What counts as a qualified appointment?
Applications
[enter]
Which source is authoritative?
Closed loans
[enter]
What attribution window is being used?
Opt-outs and suppressions
[enter]
How quickly are they removed from future actions?
Illustrative calculation using labeled assumptions
The following is a synthetic example for showing the math. It is not a BNTouch customer result or an industry benchmark.
Stage
Illustrative count
Rate
Total records selected
1,000
100% of cohort
Records passing review
620
62% of cohort
Records reached
500
80.6% of reviewed records
Unique responses
25
5% of reached records
Appointments
10
2% of reached records
Applications
4
0.8% of reached records
Closed loans
1
0.2% of reached records
The point of this example is not the result. The point is that every rate can be traced to a defined stage. A report that says “1% recapture” without showing the cohort and denominator is not comparable to this worksheet.
The 30/60/90-day measurement plan
Period
Primary job
Output
Days 1-30
Clean and classify the database.
Segment definitions, suppression rules, missing-data list, and a small review queue.
Days 31-60
Run controlled workflows by segment.
Approved message variants, reviewed send queue, responses, appointments, and opt-outs.
Days 61-90
Measure, refine, and operationalize.
Segment-level performance view, ownership, follow-up rules, and next test plan.
Days 1-30: make the database usable
Start with a representative sample before attempting a full cleanup. Separate current borrowers, past clients, partners, leads, duplicates, invalid records, and records requiring review.
Record relationship type and owner.
Record source and last meaningful interaction.
Capture known loan or milestone context without guessing missing facts.
Mark unknown, suppressed, and needs-review states explicitly.
Document which field is authoritative when systems disagree.
Days 31-60: run small, reviewable workflows
Choose one or two segments with enough context to support a useful test. Before sending anything, document why the record is included, what the message is intended to accomplish, which facts are known, which channel is approved, how opt-outs are handled, who reviews the queue, and how the workflow is paused.
AI can help summarize records, suggest segments, or prepare drafts for review. It should not be treated as proof that a person is eligible for outreach or that a message is appropriate for every channel.
Days 61-90: turn learning into a repeatable process
Compare segments by more than send volume. Track positive responses, qualified appointments, applications, closings, opt-outs, suppressions, data corrections, and time to human follow-up. Report the cohort and attribution window with every result.
What the CRM needs to support
A mortgage CRM should help the team see relationship context, create a review queue, record why a segment was selected, apply suppression, assign ownership, and measure outcomes. It should make it easier to stop or correct a workflow.
The existing BNTouch 90-day database recapture workflow provides the operating sequence. The BNTouch facts page provides product terminology. Request a configuration-specific review before treating any product capability as included in a particular plan.
FAQs
What is a good mortgage database recapture rate?
There is no universal rate without a defined cohort, channel, time period, eligibility rule, and attribution window. Calculate your own baseline first.
How many past borrowers should a loan officer contact first?
Start with a small, well-understood sample that the team can review and measure. The right size depends on data quality, ownership, channel, and follow-up capacity.
Is database recapture the same as trigger leads?
No. Database recapture concerns a known relationship database. Trigger-lead rules concern a different source and use of consumer report information.
Can a CRM automate database recapture?
A CRM can support segmentation, reminders, approved campaigns, suppression, and measurement. Automation does not remove the organization’s responsibility to review the data, message, channel, and policy.
