Tam From Verified Data

Build a verified TAM from Lusha's database. Take an ICP, return company counts, contact coverage, and signal density by segment. Break into TAM, SAM, and SOM. Make every number traceable to real data.

Input

The user will provide via $ARGUMENTS:

• ICP definition: industry, company size range, geography, funding stage, company type
• Target buyer: function and seniority (e.g. "VP of Sales, Head of RevOps")
• Segments to break down by: [optional] — default is industry, size, geography, funding stage
• What you sell: [optional] — used to calculate SOM based on signal activity in the market
• Exclusions: [optional] — industries, geographies, or company types to exclude from the TAM

If ICP definition is missing, ask once for the minimum: industry, company size range, and geography. Never estimate or interpolate — only return what Lusha can verify.

Workflow

1. TAM DEFINITION Translate the ICP into Lusha search parameters:

   • Industry and sub-verticals
   • Employee count range
   • Geography: country, region, or global
   • Funding stage if specified
   • Company type: public, private, PE-backed, etc.
   • Apply exclusions if provided

2. COMPANY COUNT — TAM Run the full TAM query via Lusha:

   • Total companies matching all ICP criteria
   • Break down by each segment dimension:
     • By industry / sub-vertical
     • By company size band
     • By geography
     • By funding stage
   • Flag any segments where Lusha coverage may be thinner — e.g. specific geographies or niche sub-verticals

3. CONTACT COVERAGE For each segment, return verified contact counts:

   • Total VP+ contacts in Lusha's database
   • Breakdown by seniority:
     • C-suite
     • VP
     • Director
     • Manager
   • Coverage ratio: contacts per company (high coverage = easier to prospect, low coverage = higher prospecting investment)

4. SIGNAL DENSITY For each segment, check current signal activity:

   • Funding events in last 90 days
   • Executive moves in last 30 days
   • Hiring surges — 10%+ headcount growth
   • Intent signals above score 60
   • Rank segments by signal density: High / Medium / Low

5. SAM CALCULATION Narrow TAM to serviceable addressable market:

   • Apply must-have ICP criteria only
   • Remove segments flagged as thin coverage
   • Remove segments with consistently low signal density unless user specifies otherwise
   • Return SAM company and contact counts

6. SOM CALCULATION Narrow SAM to serviceable obtainable market:

   • Filter to companies with active signals only (signal score 60+ in last 90 days)
   • These are the accounts most likely to convert in the near term
   • Return SOM company and contact counts
   • Note: SOM will change quarterly as signals shift — recommend re-running each quarter

7. SEGMENT PRIORITIZATION Rank all segments by combined score:

   • Company count (size of opportunity)
   • Contact coverage ratio (ease of penetration)
   • Signal density (near-term pipeline potential)
   • Return top 3 segments to prioritize first

Output Format

TAM summary

TAM breakdown by segment

By industry

By company size

By geography

By funding stage

Segment prioritization

Ranked by combined score of size, coverage, and signals:

1. [Segment] — [reason: largest signal density / strongest coverage / highest company count]
2. [Segment]
3. [Segment]

Data coverage notes

Flag any segments where Lusha's coverage is thinner than the rest of the TAM — specific geographies, niche sub-verticals, or company types where the count may underrepresent the true market size.

Recommended next step

Based on the TAM output, suggest:

• Which segment to build the first territory from
• Which play or skill to run next (e.g. Build territory plan, Find lookalike accounts, Get 10 best accounts this week)

From Lusha's Campus plays library: https://www.lusha.com/campus/plays/tam-builder-skill/