Investment risk for a digital marketer (Part 1: intro)

Posted by on November 09, 2018 · 2 mins read

When marketers calculate returns for UA campaigns, they become more accurate in predicting return performance over time. In an “infinite budget” scenario marketers will run all campaigns where ROI > 0. The issue is that infinite budget scenarios are not real. If a marketer is constrained by a budget, campaigns that return similar values on ROI can deceptively lead to non-optimal capital allocation.

Consider scenarios A and B. In both scenarios, groups of 1000 users are acquired that have the same demographic traits and the costs of acquisition. The difference is group A was acquired from a different channel than group B. Once acquired, we observe a key difference in spending behaviors of the different groups. In group A a single user generates $1000 of revenue while in group B all 1000 users generate $1 of revenue. Mathematically speaking, the return on both groups are the same 1 user x $1000 = 1000 users x $1. However, there is a clear preference which group is more valuable. When an investor has a preference to the type of return that’s generated from different investments, they need to understand the risk associated with each investment.

In the scenario above, intuitively a marketer would prefer the revenue that comes from group B because more of the user base monetized and is less risky. Measures for risk can ultimately vary depending on what the marketer and investor is optimizing for, but the discussion of investment risk is an important one when acquiring users from paid acquisition sources. Not all LTV can be treated the same when allocating capital.

In following posts we will talk about different ways that digital marketers can think about and quantify risk as a way to determine the best capital allocation for their digital properties.

The main quantification that can be done is around:

  • LTV & revenue quality
  • LTV & revenue predictability
  • Benchmarks