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How to Use Conditional Logic in Workflows

Conditional logic lets your automated workflows make decisions. Instead of running the same steps for every input, conditions evaluate data values and route execution down different paths based on the result. A lead routing workflow uses conditions to send high-value leads to the sales team and low-value leads to an email nurture sequence. A support workflow uses conditions to escalate urgent tickets and auto-respond to routine ones. Every workflow that handles more than one scenario needs conditional logic.

What Conditional Logic Does in a Workflow

A condition is a checkpoint in your workflow that asks a yes-or-no question about the data flowing through it. Is the order total above $500? Does the customer's email domain match a known enterprise company? Did the AI model classify this message as "urgent"? Based on the answer, the workflow follows one path (the "true" branch) or another (the "false" branch).

Without conditions, every workflow is a straight line: trigger fires, step 1 runs, step 2 runs, step 3 runs, done. Every input gets the same treatment. With conditions, the workflow becomes a tree with multiple branches, each handling a specific scenario. The trigger fires, steps 1-3 run for everyone, then a condition splits execution: qualified leads get steps 4a-7a (personal outreach) while unqualified leads get steps 4b-5b (automated nurture). The same workflow handles both scenarios without human judgment.

Types of Conditions

Value Comparisons

The simplest conditions compare a variable to a fixed value. These handle most rule-based decisions:

Equals: Does the status field equal "active"? Does the country code equal "US"?
Greater/less than: Is the order total above $100? Is the lead score below 30?
Contains: Does the message body contain the word "urgent"? Does the email address contain "@enterprise.com"?
Is empty/exists: Did the customer provide a phone number? Is the optional field blank?
Matches pattern: Does the input match a specific format (phone number pattern, email pattern, URL pattern)?

Value comparisons are fast, predictable, and cost nothing extra to evaluate. Use them for every decision that can be expressed as a simple comparison. Reserve more complex condition types for decisions that require interpretation.

Combined Conditions (AND/OR)

Real business decisions often involve multiple factors. A discount might apply only when the order total exceeds $200 AND the customer has been active for more than 90 days AND the product category is not "clearance." Combined conditions let you evaluate multiple criteria in a single condition node.

AND conditions: All criteria must be true for the condition to pass. "Order above $200 AND customer active AND not clearance" only routes to the discount path if every single check passes. If any one fails, execution follows the false path.

OR conditions: At least one criterion must be true. "Customer is enterprise tier OR order above $1000 OR manually flagged as VIP" routes to the priority path if any of the three checks pass. This is useful when multiple different signals should trigger the same response.

You can nest AND and OR conditions for complex logic: "(order above $500 AND customer active) OR (customer is enterprise AND any order amount)." Nesting adds power but also adds complexity, so keep your conditions as simple as the business logic allows.

AI-Powered Conditions

When the decision requires understanding unstructured text, sentiment, or context, traditional value comparisons fall short. You cannot reliably detect customer frustration with a keyword search, because a customer might write "This is absolutely the worst experience I have ever had" without using any word on your keyword list.

AI-powered conditions send the data to an AI model with instructions like "Classify this customer message as POSITIVE, NEUTRAL, or NEGATIVE" and use the AI's response as the condition value. The workflow then branches based on the classification: positive messages get a thank-you, neutral messages get logged, negative messages get escalated to a human.

AI conditions are more expensive and slower than value comparisons (they require an API call to the AI model), so use them strategically. Filter with cheap conditions first (is the message blank? is this a known spam domain?), then apply AI classification only to messages that pass the initial filters. See How to Add AI Decision-Making to Workflows for detailed implementation guidance.

Switch/Multi-Way Conditions

An if/else condition has two outputs: true and false. A switch condition has multiple outputs, one for each possible value. If you need to route support tickets to different departments based on category (billing, technical, sales, general), a switch condition with four outputs is cleaner than three nested if/else conditions.

Switch conditions work best when the variable has a known set of possible values (department names, status codes, plan tiers, geographic regions). Each value maps to its own branch with its own action sequence. An "other/default" branch catches any values that do not match the specified options.

Practical Condition Patterns

Pattern 1: Tiered Response

Route different levels of service based on customer value. Enterprise customers get human outreach within 15 minutes. Professional customers get a priority queue and response within 2 hours. Free-tier customers get an automated response with a link to the knowledge base.

The condition checks the customer's plan tier (retrieved from a database lookup earlier in the workflow) and branches into three paths. Each path has its own action sequence optimized for that customer segment. This pattern works for support routing, sales follow-up, onboarding flows, and notification preferences.

Pattern 2: Threshold-Based Escalation

Auto-handle routine cases and escalate exceptions. If the refund amount is under $50 and the customer has no previous refund history in the last 90 days, process it automatically and send confirmation. If the amount is above $50 or the customer has multiple recent refunds, route to a manager for review.

The condition combines an amount threshold with a history check. The automatic path handles 80-90% of cases without human involvement, while the escalation path catches the 10-20% that need judgment. This pattern applies to approvals, credit adjustments, exception handling, and policy enforcement.

Pattern 3: Content-Based Routing

Direct incoming messages to the right team based on what the message is about. An AI classification step categorizes the message (billing question, feature request, bug report, partnership inquiry, spam), and a switch condition routes each category to the appropriate team with the appropriate response template.

This pattern replaces the manual inbox triage that someone on your team currently spends 30-60 minutes on every morning. The AI handles the categorization with 90-95% accuracy, and the routing happens instantly. The 5-10% of messages the AI is unsure about get routed to a human triage queue. See How to Categorize Tickets with AI.

Pattern 4: Time-Based Conditions

Different actions depending on when the event occurs. If a support ticket arrives during business hours (9 AM to 6 PM in the customer's timezone), route to the live support queue. If it arrives after hours, send an auto-acknowledgment, create the ticket, and queue it for the next business day.

Time-based conditions are also useful for campaigns (different messaging for weekday vs weekend submissions), SLA monitoring (has this ticket been open for more than 4 hours without a response?), and scheduled workflows that need to skip holidays or weekends.

Designing Clean Conditional Logic

Put cheap conditions before expensive ones. If your workflow needs to check whether a message is from a valid email AND whether the AI classifies it as a complaint, check the email validity first. The email check costs nothing and eliminates invalid entries. The AI classification costs tokens and takes time. Filtering with the cheap check first means you only pay for AI classification on valid messages.

Avoid deeply nested conditions. Three levels of nesting (if A, then if B, then if C) are manageable. Five or more levels become nearly impossible to debug. If you find yourself nesting deeply, look for ways to flatten the structure: use a switch condition instead of nested if/else, combine conditions with AND/OR instead of nesting them, or split the workflow into sub-workflows.

Always include a default path. Every condition should handle the case where none of the specified values match. A switch condition routing by department should have an "other" branch that logs the unexpected value and alerts someone. Without a default, unexpected inputs cause the workflow to silently end without completing its job.

Name conditions descriptively. "Check Value" tells you nothing when you return to the workflow in three months. "Is Order Above $500" or "Is Customer Enterprise Tier" tells you exactly what the condition evaluates. Good names make the workflow canvas self-documenting.

Test every branch. Run test data through each possible path, not just the happy path. If you have a condition with three branches, test all three. If you have nested conditions creating six possible paths, test all six. Untested branches are where bugs hide in production.

Performance tip: Conditions themselves execute in microseconds. The cost is in what each branch does, not in the branching itself. Do not hesitate to add conditions that save expensive operations (API calls, AI classification, email sending) from running on inputs that do not need them. A well-placed condition that filters out 70% of inputs before an AI step reduces your AI costs by 70%.