Filters and Response to Source

Feature Snapshot

Summary:
Filters are processing steps within a LeadConduit flow that dynamically evaluate lead data against predefined rules and, when matched, halt further processing while sending an immediate, customized response back to the source.

Key Benefits:

• Protect buyers by blocking unwanted or low‐quality leads
• Provide immediate, clear feedback to the source to improve future submissions

Typical Use Cases:

• Halting lead processing based on complex, multi-condition business logic
• Returning specific error messages (e.g., “Obscenity detected” or “Invalid data pattern”) to provide sources with real-time feedback for optimization
• Blocking leads that dont meet vendor contracted or business rules for purchase

How the Filters and Response to Source works?

Filters have only one function: They decide whether to let the lead proceed on to the next step in the flow, or stop the lead at that point and issue a response, “failure” by default, back to the Source. Without filters, a lead will continue processing and respond to the source with “success”, usually signaling that they buyer has purchased the lead. Think of it as the critical decisioning step. Filters operate within a LeadConduit flow by inspecting incoming lead data using operators such as “is equal to”, “contains”, or “matches regex”. When a lead’s field values satisfy the specified criteria (for instance, containing disallowed obscenities), the filter immediately stops further processing. It then triggers a response using preconfigured parameters—typically setting the lead status (e.g., “failure”) and a detailed rejection reason—to notify the source precisely why the lead was blocked. This immediate response mechanism protects downstream systems and informs the source so they can adjust their submission process.

Step‑by‑Step Instructions

1. Add the Filter Step:
   Navigate to your flow’s Steps list, click “Add to Flow”, and select “Filter” from the available options. Place the filter after enhancement steps but before critical recipient steps.

2. Configure Filter Rules:
   Click “Add Rule” within the filter configuration. Select the lead field you wish to evaluate (for example, a comments field), choose an operator such as “contains” or “matches regex”, and enter the value or list of terms (such as a list of obscene words).

3. Define Response Parameters:
   Configure the filter’s response by selecting a lead status (typically “failure”) and entering a custom rejection reason (e.g., “Lead rejected due to disallowed language” or “Obscenity detected”). These parameters determine what message the source will receive.

4. Save and Position the Filter:
   Click “Save” on the filter configuration, then drag and drop the filter step to the appropriate position in your flow so that it intercepts leads before costly processing steps begin.

5. Integrate with Flow Response Logic:
   Ensure the filter is connected to the response mechanism so that if a lead meets the filter’s criteria, processing stops immediately and the configured response is sent to the source.

Expected Result:
When a lead is submitted that meets any filter rule (for example, by containing disallowed terms), the flow halts at the filter step. The source immediately receives a response indicating the lead was rejected, with a status (e.g., “failure”) and a clear rejection reason (e.g., “Obscenity detected”).

Validation & Monitoring (optional)

• Test the Setup: Submit a test lead containing flagged content (such as an obscene term) to ensure that the filter halts processing and sends the correct response.
• Where to Monitor?: Check the Events tab in your LeadConduit dashboard for the filter event details, which will show the lead status and rejection reason, and set up email or dashboard alerts as needed.

Best Practices

• Use explicit, narrowly defined rules rather than broad conditions to minimize false positives.
• Regularly update your list of disallowed terms or regular expressions as industry standards and partner requirements evolve.
• Position filters as early in the flow as possible to save processing costs and protect downstream integrations.
• Document the purpose and configuration of each filter for future troubleshooting and audits.
• Test filters with a variety of inputs—including edge cases—to ensure good leads are not unintentionally rejected.

Troubleshooting

Frequently Asked Questions (FAQ)

What exactly is a filter in LeadConduit?

A filter is a processing step within your flow that evaluates lead data against predefined rules. If the rules are met, the filter stops further processing and returns an immediate response (usually indicating failure) to the source.

Why are filters important for responding to the source?

Filters are crucial because they provide instant, actionable feedback to the source. This ensures that any issues—such as the presence of obscenities or noncompliant data—are communicated immediately, allowing sources to adjust and resubmit higher-quality leads.

How do filters impact the response sent back to the source?

When a filter condition is met, it halts the lead processing and triggers a response that includes a specific status (commonly “failure”) and a detailed rejection reason. This informs the source what was wrong with the submitted lead.

How do I filter obscenities in my Flow?

To filter obscenities, add rules in your filter step that target fields likely to contain user-generated content. You can use operators like “contains” or “matches regex” to identify and block words from a predetermined list of disallowed language.

How is the response to the source determined?

The response is determined by the filter’s configuration. If a lead meets the filter criteria, the filter stops processing and uses its configured response parameters—setting a lead status and custom rejection reason—to generate the reply sent back to the source.

Why is it important to respond to the source when a lead is filtered?

Responding to the source is essential because it provides clear, immediate feedback. This transparency helps sources understand exactly why a lead was rejected, enabling them to correct data errors, reduce future rejections, and ultimately improve the overall quality of submitted leads.

Glossary