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Turn spend down to test it
Spend and lag
Spend today converts to revenue after a lag, around 14 days in one example. Plotting total spend against ARR, and how elastic that relationship is, shows whether to pour fuel on the fire or pump the brakes. A common failure is dialing spend up to 13 on a scale of 10, so that much of it could have been absent with the same results, which only hands money to Meta and Google.
Seeing the whole
Few growth people can see the whole picture. Many are experts in a single channel, and the interrelationship of ad spend, sponsorships, podcast features, and PR is what decides whether spend is elastic.
Testing the mix
Later on, the right organic mix is around 35% to 45% of acquisition coming from word of mouth, organic, and discovery. If turning paid off makes growth fall, the SEO, AEO, and reviews have been forgotten. Past a million dollars a month in spend, a marketing mix model and incrementality testing should say which channels are incremental. The model starts out wrong. Dialing things down and running holdouts shows whether it proves true, and it improves over time.
How does a holdout test measure ads?
A holdout test withholds ads from a randomly chosen group and compares its results to a group that saw them. The gap between the two groups is the effect the ads caused. A 2011 Google research paper described a geographic version, where entire regions receive different ad levels. Because assignment is random, the comparison filters out sales that would have happened anyway.
Where did the marketing mix come from?
Harvard professor Neil Borden popularized the phrase marketing mix in a 1964 article. He credited colleague James Culliton, who in 1948 described a marketing executive as a mixer of ingredients. The idea grew into the four Ps of product, price, place, and promotion, which E. Jerome McCarthy proposed in 1960. Statistical marketing mix models use time series of spending and sales to estimate each channel's contribution. Meta released an open-source one called Robyn in 2021.
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