Lookalike Audience Pool Calculator

Estimate addressable reach when scaling lookalike audiences by market.

Addressable users in the country/region.
%
1% = tightest match, 10% = broadest.
Customers/leads you build the model from.
Addressable pool
1,200,000
3% lookalike
Seed quality
Usable
Ideal ≥ 5,000
Tighter 1% pool
400,000
Highest-similarity option

A 2,500 seed works but isn't robust. Your 3% lookalike spans ~1,200,000 people, start at 1–2% and widen only if it converts.

Seed purity beats seed size, a lookalike of your best-LTV customers outperforms a bigger list of all buyers.

About this calculator

A lookalike audience is only as good as the seed it was built from, a broad reach percentage built on a thin, noisy seed list produces a large but low-signal audience. This calculator sizes your addressable lookalike pool from market population and match percentage, then separately grades your seed list against the volume a platform actually needs to build a clean model.

How to use it

  1. Enter your target market population, the addressable users in the country or region you're targeting.
  2. Enter your lookalike percentage, tighter percentages (1%) match closer to your seed, broader ones (10%) trade precision for reach.
  3. Enter your seed audience size, the customers or leads the model is built from.
  4. Read the addressable pool size and your seed quality grade, and use the tighter 1% pool as the higher-precision reference point.

Methodology

Addressable pool is market population × lookalike percentage, a direct scaling of the total population by the match tightness you selected.

Seed quality is graded against two thresholds: below 1,000 the seed is flagged as too small (the model will likely be noisy), between 1,000 and 5,000 it's usable but not robust, and 5,000+ is considered a strong, reliable seed.

The 1% pool is shown separately as a reference, since it represents the tightest, highest-similarity match available regardless of what broader percentage you're currently modeling.

This is a volume calculation, it says nothing about seed quality beyond size. A seed of 5,000 low-value trial users will still produce a weaker lookalike than a seed of 1,500 high-LTV repeat customers, seed composition matters as much as seed count.

FAQ

Why does a smaller lookalike percentage produce a better-quality audience?

A 1% lookalike selects only the users most statistically similar to your seed, a 10% lookalike casts a much wider net that includes progressively less similar users to hit the larger reach target. Tighter percentages sacrifice reach for precision.

My seed list is below the recommended minimum, what should I do?

Widen what counts as a seed event, include high-intent actions (add-to-cart, demo request) alongside purchases, combine multiple markets if you're targeting internationally, or wait to accumulate more volume before building the lookalike, a noisy small seed often performs worse than no lookalike at all.

Should I always start with a 1% lookalike?

It's a reasonable default when seed quality is high, since it gives you the highest-similarity audience to test first. If it's too small to spend efficiently, widen gradually (2%, then 3%) only after confirming the tighter tier is converting well.

Does seed purity matter more than seed size?

Generally yes. A lookalike built from your best-LTV customers specifically will typically outperform a larger lookalike built from every buyer regardless of value, quality of the input signal compounds through the whole modeled audience.