Decision emails are the turning point in a deal. They carry approvals, declines, counteroffers, and stipulations that dictate the next move. When these arrive in crowded shared inboxes, teams waste time opening threads and deciphering free text.
Small delays create missed callbacks, stale offers, and poor broker experiences.
Heron automates classification for decision emails from the moment they arrive. The system reads subject lines, bodies, and attachments to identify whether the message is an approval, decline, conditional offer, or request for more information.
It applies a clear decision label, extracts key context, and links the email to the right record. This creates instant clarity for brokers and funders and keeps pipelines moving without manual sorting.
With reliable classification in place, operations teams get real-time visibility on outcomes. Underwriters know which deals need action, and brokers get faster responses that help close more funding opportunities.
Use Cases
- Identify decision type on arrival: Heron recognizes approvals, declines, counteroffers, and stipulations as soon as emails hit the inbox. It applies a decision label that drives routing and next steps.
- Differentiate soft and hard decisions: The system classifies messages that say a deal is pending conditions vs fully approved or declined. This helps teams pick the right follow-up path.
- Classify attachment-based decisions: Many funders send PDF letters. Heron reads those attachments, extracts signals, and applies accurate decision tags.
- Handle multi-deal threads: Long threads sometimes include several decisions. Heron splits decisions by merchant and classifies each message correctly.
- Spot non-decisions that look like decisions: Some replies are clarifications or meeting notes. Heron classifies these as non-decisions to avoid status confusion.
- Mark stip-driven decisions: Messages that include conditions or stips get a dedicated label. This classification feeds the stip workflow automatically.
These patterns remove guesswork and make sure each decision is labeled and visible the moment it arrives.
Operational Impact
Classification reduces noise and speeds action across busy teams.
- Speed: Decisions are labeled in seconds, which compresses response times across the board.
- Accuracy: Consistent classification removes subjective inbox reading and reduces misrouted work.
- Scalability: High-volume days do not slow down, since labeling is automatic and reliable.
- Visibility: Dashboards reflect the real decision mix by broker, funder, and program in real time.
- Compliance: Labels create an auditable trail of what came in and how it was handled.
Funders move faster when outcomes are obvious. Brokers see cleaner handoffs, fewer email loops, and prompt next steps.
How Classification Works for Decision Emails in Heron
Heron runs classification in line with intake, so outcomes are clear before anyone opens the email.
- Ingest and detect: Messages arrive via shared inbox forwarding or API. Heron detects decision intent from subjects, bodies, and attachments. It uses pattern and phrase matching tuned for MCA and small business funding.
- Apply the decision label: The system assigns a primary label like Approved, Declined, Conditional, or Information Requested. Secondary tags can include Stips Required, Counteroffer, or Program Specific.
- Link to the right record: Heron matches the decision to the merchant or opportunity using email addresses, IDs, names, and prior thread context. If needed, a quick review queue handles odd cases.
- Attach structured context: Classification stores key message pointers like sender domain, funder name, and timestamp. This sets up parsing, routing, and write back steps.
- Trigger the downstream flow: Labels drive next actions. An Approved label triggers status updates. A Conditional label opens a stips track. A Declined label moves the deal into a post-decision path.
This creates a clean signal for each message, so teams do not have to read every thread to interpret the outcome.
Decision Taxonomy and Label Design
Clear labels drive consistent outcomes. A simple taxonomy works best for mixed-volume teams.
- Primary outcome labels: Approved, Declined, Conditional Offer, Information Requested. These labels define the path and the urgency.
- Contextual sublabels: Stips Required, Counteroffer, Program Fit, Offer Expiring. These add nuance that helps teams act quickly.
- Thread state labels: New Decision, Updated Decision, Superseded Decision. These labels handle revisions and prevent confusion.
- Process labels: Parsed, Routed, Written Back. These signal pipeline positions without clogging operational notes.
A light taxonomy avoids label inflation and keeps reporting strong.
Collaboration and Broker Experience
Classification makes broker communication crisp and timely.
- Fast feedback to brokers: When a decision is labeled, the system can notify the broker right away. This cuts hours of idle time.
- Less back-and-forth: Clear decision tags reduce questions like “Is this final” or “What is still needed.” Teams reply with specifics.
- Predictable expectations: Brokers learn what each label means and act quickly on stips or signatures.
- Cleaner escalations: If a decision shifts, the new label supersedes the old one. There is no confusion about which message is current.
Stronger communication increases close rates and reduces stress for both sides.
Data Quality and Compliance
Email classification improves control without adding manual work.
- Full traceability: Every label carries a timestamp, sender, and linkage to the deal record.
- Consistent language mapping: Free text becomes uniform categories in the CRM. This supports analytics and audit checks.
- Secure processing: Decision content is handled in a SOC 2 environment with encrypted storage and transport.
- Error handling: Low-confidence labels route to a review queue. Users correct the label once, and pattern learning improves next time.
These controls give compliance teams confidence without slowing operations.
Performance Metrics and Analytics
Classification creates new visibility into decision flow and partner performance.
- Decision mix by funder: Track how often a funder sends approvals, declines, and conditional offers. This informs program alignment.
- Time to action: Measure minutes from decision arrival to status change or broker notice. This highlights operational gains.
- Label accuracy and overrides: Monitor how often reviewers change labels. Use that signal to tune patterns.
- Offer aging and expiry risk: See which conditional decisions sit too long. Drive reminders or re-engagement.
- Broker experience indicators: Track how fast brokers receive updates after a label appears. Improve response playbooks.
These insights build a culture of speed and clear ownership.
Implementation Best Practices
Teams get better results when they set simple rules and keep improving them.
- Start with four primary labels: Approved, Declined, Conditional Offer, and Information Requested. Expand only when needed.
- Map labels to actions: Decide what each label does in the CRM and who gets notified. Do not leave it vague.
- Use seed phrases from real mail: Pull examples from current funders to tune the first pass.
- Review edge cases weekly: Look at low-confidence or corrected labels and adjust patterns.
- Add broker feedback where useful: If brokers ask the same question, consider a sublabel or a playbook update.
- Keep dashboards simple: Focus on decision mix, time to action, and label accuracy. Avoid vanity metrics.
A light, iterative rollout delivers quick wins and builds trust in the automation.
Operational Impact Scenarios
Different decision patterns create different workloads. Classification handles each cleanly.
- Batch approvals at day's end: Labels drop on dozens of messages at once. Routing and status updates fire without human triage.
- Conditional offers with long stip lists: A Conditional label plus Stips Required drives the stips queue automatically. Teams do not miss tasks.
- Declines that need call notes: A Declined label triggers a callback task. Notes auto-link to the deal for context.
- Mixed outcomes in one thread: Each outcome gets its own label and link. Teams know what belongs to which merchant.
These scenarios show why classification is the stable base for the rest of the workflow.
Benefits of Using Heron for Classifying Decision Emails
- Speed: Decision intent is visible right away, which cuts idle time between messages and action.
- Accuracy: Labels are consistent and reduce misinterpretation of free text.
- Scale: High volumes sort themselves, even on busy days.
- Clarity: Everyone sees the same outcome and acts on the same signal.
- Consistency: Labels drive the same downstream steps every time.
A dependable classification layer turns inbox chaos into a predictable decision engine.
FAQs About Classify for Decision Emails
How does Heron tell an approval from a conditional offer?
Heron looks for approval phrases and checks for conditions in the same message. If the content includes requirements or stips, the email is labeled as a conditional offer. This avoids marking a deal as fully approved when follow-up work is still needed.
Can Heron classify decisions that arrive only as PDF letters?
Yes. Heron reads the attached letter and pulls decision signals from the document text. It applies the correct decision label and attaches a summary so teams can act without opening the file.
What if a thread contains two different merchants and two different decisions?
Heron splits the thread by merchant identifiers and labels each decision separately. Each label links to the correct deal record, which prevents cross-posting in the CRM.
How are misclassifications corrected?
Low-confidence labels land in a review queue. A user selects the correct label once, and pattern learning improves future matches on similar emails. This keeps accuracy high while keeping the process light.
How does classification help downstream steps like routing and write back?
Labels are triggers. Approved moves the deal forward, Conditional opens the stips track, and Declined starts a callback or closeout path. Because the label is structured, write back to the CRM is clean and immediate.
