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Overview

While Bitscale provides a set of preset signals and filters to help you build your first lists, advanced outbound workflows often require hyper-specific targeting. As SDRs and GTM teams exhaust broader TAM lists, they need to identify niche accounts and personas using custom conditions. Bitscale enables you to stack enrichments, AI layers, and signals to create these custom filters directly in your grids, allowing you to prioritize accounts with the highest buying intent.

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When to Use

  • Your TAM is largely covered and you need more granular targeting.
  • You want to identify high-intent accounts using multiple conditions.
  • You need to validate specific traits (e.g., tech stack, hiring activity, product signals).
  • You want to score and segment accounts into different outbound campaigns.

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Step 1: Start with a Base List

  1. Use Find Companies to generate an ICP-aligned list.
    • Example filters:
      • Employee count: 200–500
      • Geography: United States
      • Industry: Software (optional)
  2. Import results into a grid.
  3. Expand by fetching additional rows (up to your search limits).

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Step 2: Add Custom Intent Signals

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Example 1: Hiring SDRs

  • Enrichment: Active Jobs (Company-Level)
  • Prompt (AI Layer):
    “Check whether @company_name is hiring for sales roles.”
  • Output Format: Boolean (True/False)
Use Case: Hiring SDRs signals growth and a need for enablement tools.

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Example 2: Tech Stack Validation

  • Enrichment: BuiltWith (Company URL → Tech Stack)
  • Initialize technologies into a clean column.
  • AI Layer Prompt:
    “Check whether Salesforce or HubSpot is mentioned in the below list.”
  • Output Format: Boolean (True/False)
Use Case: Prioritize accounts using CRMs that integrate well with your product.

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Example 3: Product Feature Check

  • Enrichment: BitAgent (Website Scrape)
  • Prompt:
    “Check whether @company_website has a login feature.”
  • Output Format: Boolean (True/False)
Use Case: Identify companies with SaaS/product platforms by validating if they support login functionality.

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Step 3: Layer Filters Together

Each custom filter acts as a scoring layer:
  • Hiring SDRs = Growth Signal
  • Uses Salesforce/HubSpot = Tech Fit
  • Has Login Feature = Product-Led SaaS
Accounts meeting multiple conditions rise to the top of the pecking order for outbound campaigns.

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Step 4: Prioritize & Segment

  • High Intent Accounts: Meet multiple signals (e.g., GitHub hiring sales roles + using Salesforce + SaaS login).
  • Medium Intent Accounts: Match one or two conditions.
  • Low Intent Accounts: Remain in the grid for future nurturing or broad campaigns.

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Best Practices

  • Start broad, then chip away with layered filters.
  • Use Boolean outputs (True/False) for clarity and easy run conditions.
  • Combine hiring, tech stack, and product validation for strong intent scoring.
  • Keep grids clean by adding validated signals as separate columns.
  • Iterate — custom filters will evolve as your outbound strategy matures.

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Summary

Custom Filters and Signals in Bitscale let you go beyond preset enrichments to design hyper-specific targeting workflows. By combining hiring data, tech stack insights, product validation, and AI logic, you can create multi-layered account scoring systems and prioritize outreach where intent is highest. For help designing advanced filters, reach out via the Bitscale support channel.