Multi-touch attribution distributes credit for a sale across several marketing interactions rather than assigning it all to one. Models vary in how they weight each touch, using linear, time-decay, or position-based rules. It gives a fuller picture of the buying journey at the cost of added complexity.

Multi-touch is more honest than single-touch because real buyers touch many things before they buy. It is also more complex, and complexity invites false precision. The weighting is still a judgment call dressed as math. Use it to understand the shape of the journey, not to settle arguments about which channel deserves more budget.

Example:

A journey of content, an ad, and a sales call splits credit across all three rather than handing it to whichever came first or last.

How does multi-touch attribution assign credit?

By rules that weight each interaction, such as splitting evenly (linear), favoring recent touches (time-decay), or emphasizing first and last (position-based).

Is multi-touch attribution worth the complexity?

It better reflects real buying journeys, but the weighting remains a judgment call. Treat it as directional insight rather than precise proof.