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.
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.
| Cometly | Epoyo | |
|---|---|---|
| Unit of attribution | Ad, ad group, campaign | Individual organic post |
| Where the data starts | Ad platform reporting | Content account statistics |
| Multi-touch modelling | Central to the product | Four confidence tiers; verified has to be earned |
| Useful with zero ad spend | Little to report | This is the intended case |
| Answers what to post next | Not its purpose | Yes, 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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