Epoyo vs Cometly

Cometly attributes ad spend to revenue across long sales cycles. Epoyo attributes organic posts to revenue. The split is paid against organic, not better against worse.

Cometly is described as ad attribution. Checked 12 August 2026.

What Cometly is for

Cometly is an ad attribution platform, with particular strength in longer B2B cycles where a click and the revenue it eventually produces are separated by weeks. Server-side tracking and multi-touch models are the core of what it does.

Where Epoyo differs

Epoyo starts where there is no ad to attribute. An organic post has no campaign ID, no ad group and no spend, so the entire apparatus of ad attribution has nothing to hang a conversion on. Epoyo attributes to the post itself.

 CometlyEpoyo
Unit of attributionAd, ad group, campaignIndividual organic post
Where the data startsAd platform reportingContent account statistics
Multi-touch modellingCentral to the productFour confidence tiers; verified has to be earned
Useful with zero ad spendLittle to reportThis is the intended case
Answers what to post nextNot its purposeYes, from campaigns graded by the evidence behind them

Choose Cometly if

  • Paid acquisition is your main channel and you need multi-touch models across it.
  • You have a long B2B cycle where server-side ad tracking is the missing piece.
  • Your reporting is organised around campaigns because your spending is.

Choose Epoyo if

  • Your growth comes from posting, not from buying impressions.
  • You want each campaign's result graded by the evidence behind it rather than by a model.
  • You would rather see an estimate labelled as one than a modelled number that cannot be questioned.

Common questions

Can I use both?
Yes, and for a business running both channels seriously that is often the right setup. They measure different acquisition motions and neither substitutes for the other.
Does Epoyo do multi-touch attribution?
No. Every campaign carries an attribution confidence, and the top tier is only reached when a tracked link was followed or your product sent an event naming that campaign. A correlation in time never rises above possible-influence, however convincing it looks. A modelled number that looks precise is harder to argue with than a labelled estimate.

Compare them on your own numbers

The free analysis takes a link and no account, which is the fastest way to judge any of this.

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