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How to Create a Signal Agent for New Product Launches

Use the New Product Launch signal to detect companies that have officially announced a new product release. This Explorium-powered signal helps you spot accounts that are actively innovating, expanding their portfolio, and showing strong buying intent.

By the end of this tutorial, you’ll know how to create and deploy a Signal Agent that monitors companies for new product launch events, sets a daily identification limit, and routes matched companies into your workflow.


Why this matters

New product launches are high-value, event-based signals. Unlike behavioral signals like engagement or structural signals like hiring and funding, this one tells you what a company is doing right now in the market.

That makes it useful for identifying timely outreach opportunities, prioritizing active accounts, and combining event data with your existing segment filters for stronger targeting.


Prerequisites

  • You should already know how to access Signal agents in lemlist.

  • You should already have a basic understanding of lists, CSV imports, or segment targeting.

  • You should have enough credits available for signal identification.


Core lesson

Phase 1: Open the Signal Agent builder

Start by going to Signal agents from the left sidebar, then click Create signal agent. This opens the guided setup flow where you’ll choose the type of signal you want to monitor.

Signal agents page with the Create signal agent button highlighted

Phase 2: Choose the New Product Launch signal

In the signal selection step, expand Company news and select New product launch. This signal is powered by Explorium and is designed to surface companies announcing new products through public business event data.

Create signal agent modal showing Company news and New product launch selected

Phase 3: Name your agent

Enter a clear, descriptive name for your agent, then click Next. Use a name that makes the purpose obvious to your team, such as the audience, geography, or workflow it supports.

Agent configuration step with the Agent name field and Next button highlighted

Phase 4: Define the scope and daily volume

Choose the group of companies you want to monitor, then set your Identification limit. You can monitor All segments for broad discovery, a Company list for specific target accounts, or a Specific segment using a CSV file. After that, use the slider to set how many signals can be identified per day based on your goals and credit budget.

Scope step showing segment selection options and identification limit slider

Why this step matters: scope controls who gets monitored, while the daily limit controls how many results can be surfaced each day. Together, they help balance coverage, relevance, and spend.

  • Signal level: Company

  • Billing: 100 credits per identification

  • Detection cadence: Daily

  • Explorium lookback window: Last 3 months


Phase 5: Choose how signals should be processed

Select how you want matched companies to flow into your workflow. You can review signals manually, auto-create tasks, or push them into a campaign when available for your setup. If you choose task creation, configure the task type, owner logic, fallback owner, priority, title, and instructions so your team knows exactly what to do next.

Signals processing step showing Auto-create tasks and task configuration fields

Why this step matters: the signal is only valuable if it leads to action. Processing rules help you turn detections into follow-up work without needing to review every result manually.


Phase 6: Review and deploy the agent

Check the summary screen to confirm the signal type, source, billing, processing method, and scope. If everything looks correct, click Deploy agent to start daily monitoring.

Summary step showing New product launch configuration and Deploy agent button

How the signal works after deployment

Once deployed, the agent runs in daily batches and looks for companies with matching new_product events based on your selected scope and filters. Each matched company appears as a lead with signal details such as:

  • Product name

  • Event date

  • Company details

The signal uses deduplication so the same event is not surfaced multiple times unnecessarily.


What this unlocks

  • Monitor companies that are actively launching new products

  • Spot innovation cycles and expansion activity earlier

  • Prioritize accounts with strong buying intent

  • Combine event data with filters like persona, location, industry, and company size

  • Send matched companies into manual review, tasks, or campaigns


Practical example

Let’s say you sell software to product, sales, or operations teams. You can create a New Product Launch signal agent for companies in your target industries and sizes, then cap daily identification to a manageable number like 20.

Each day, your team receives fresh companies that recently launched products. That gives you a timely reason to reach out with messaging tied to product expansion, go-to-market support, onboarding, analytics, or enablement.

  • Broad monitoring: Use All segments to discover new accounts at scale

  • Target account monitoring: Use a Company list to track named accounts

  • Custom imports: Use Specific segment if you want to upload a CSV of companies to watch


Troubleshooting & pitfalls

Issue: I’m not seeing many results

  • Root cause: Your scope may be too narrow, or your segment filters may be too restrictive.

  • Fix:

    • Broaden your scope from a list to all segments if appropriate

    • Review your targeting filters

    • Increase your daily identification limit if you want more possible matches surfaced

Issue: I’m using credits too quickly

  • Root cause: The daily identification limit is set too high for your available budget.

  • Fix:

    • Lower the identification slider

    • Start with a smaller daily cap like 5 or 20

    • Focus on a narrower list or segment for better efficiency

Issue: Signals are detected, but no one follows up

  • Root cause: The processing step may not be configured for your team’s workflow.

  • Fix:

    • Use Auto-create tasks if you want immediate action

    • Set a clear fallback owner

    • Add instructions so task assignees know how to handle each lead

Issue: I’m worried about duplicates

  • Root cause: Similar company events can happen close together.

  • Fix:

    • Rely on built-in deduplication for identical event keys

    • Review repeated companies to see whether they are truly separate launches

    • Use processing rules that fit your review process

Best practices

  • Start with a moderate daily cap so you can validate quality before scaling

  • Use descriptive agent names to make reporting and collaboration easier

  • Pair this signal with firmographic filters for stronger lead relevance

  • Use task instructions that tell reps exactly how to act on a launch event

  • Review results regularly and refine your scope if quality is too broad or too narrow


Key details to remember

  • Provider: Explorium Business Events API

  • Signal type: Event-based company news

  • Supported scope types: All Segments, List, CSV import

  • Billing model: Per result

  • Credit cost: 100 credits per identified company

Use this signal when you want to catch companies at the moment they are expanding and innovating. It’s a strong addition to the Signals suite because it complements behavioral and structural signals with timely market activity.

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