3 stories tagged #mmm.
A small set of stories on this topic. Browse the latest across all topics, or jump to a more active tag below.
View all news →
B2B marketers no longer seek one attribution model to explain all revenue outcomes. According to MarTech, successful teams instead combine attribution with marketing mix modeling and experimentation to support budget and pipeline decisions.
Structural changes have lengthened B2B journeys from six or seven touches to 20 to 40 touches across multiple channels and stakeholders.
Open-source platforms have made marketing mix modeling more accessible by removing prior consulting expenses of $150,000 to $500,000. Any team with R or Python expertise and clean historical data can now run models in-house.
Almost half (46.9%) of U.S. marketers plan increased MMM investment over the next year, and they ranked it the most reliable measurement methodology at 27.6%.
A MarTech article states that effective measurement depends on connecting signals across MMM, attribution, and incrementality instead of forcing a single source of truth.
According to [MarTech](https://martech.org/why-marketing-measurement-needs-triangulation/), MMM evaluates overall business contribution and media mix allocation. Attribution focuses on user-level interactions and conversion paths. Incrementality measures whether marketing exposure actually influenced consumer behavior.