Should the revenue of organic installs be included in a ROAS calculation?

Question

It is typical that one sees some correlation between non-organic (paid) installs and organic installs. So one can assume that some portion of the organic installs are a result of non-organic (paid) installs an thus a result of UA.

There is no good way to exactly measure the ration between organic and non-organic installs but stats show that there is a certain uplift in organics if UA is scaled.

So the question arises if organic revenue should play a role in the ROAS calculation of user acquisition efforts.

Answer 1

Yes, but some things to consider:

- organic users' monetization performance often is worse than that of paid users. Applying an uplift on installs is likely skewed: if you arrive at an estimate that organic installs uplift is 0.2 of paid installs, most likely the appropriate revenue uplift factor is more like 0.1 or less (depending on how high the quality of your paid users is)

- when calculating the uplift factor, analyze your baseline granularly: search traffic that you get based on competitor or category keywords moves significantly less than search traffic for your brand. And if there is not a significantly different trend in organic traffic in countries where you run paid acquisition vs. where you don't, then likely other factors are at play. 

- we've experimented with loads of different models, and what has been working best for us is rather going aggressive on attribution lookback windows instead of applying generous static uplift factors. For example: Facebook's default setting is 28d click and 1d view attribution. If you set this to 28d click and 28d view, Facebook will already track around 20-30% more revenue than with the default setting. Of course an argument can be made that Facebook is incentivized to overstate their effectiveness (versus other channels), but I believe the accuracy of their method is still better than a static factor model. 

- In most cases I've seen and worked on, after a launch period the correlation between organic and paid traffic becomes smaller unless you change your campaign strategy (chart pushes / volume campaigns have a different organics impact than strict direct ROAS campaigns). 

- because of that last point, in general I'd advise caution unless you're in some kind of competitive landgrab situation. The potential bottom line contribution you burn by misattributing organic revenue and overspending on UA can be way more painful for your business' health than scaling a little slower. Monitor your bottom line, and if it looks like this, something's going wrong:

(these are things I have observed and applied for mobile games - I don't have experience with other types of apps)

Comments

These are all very excellent points. Thank you for sharing!

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'.... organic users' monetization performance often is worse than that of paid users'. An interesting insight. In our case organic users spend vastly more than paid users. Our rule of thouhg is that those users actively found / were directed to us and are more engaged. But it could also lead to the conclusion that our UA is collecting the wrong (in that respect) users.

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I also found surprising to read that organic users monetize a lot less. I've seen both cases, but more commonly seeing higher ARPU/retention with organic cohorts (in non-games apps).
But then every app has its own organic structure: high brand awareness, powerful keyword-ASO, TV/offline marketing, influencers, PR, featuring etc will bring very different "subtypes" of organic users.

To answer the initial question, I've seen the answer also vary quite a bit from app to app, with some getting .5 organic for every paid, to 0. Most often much higher on iOS than Android. There are multiple factors to explain this, here's a recent article I co-wrote on the topic: https://www.appsflyer.com/blog/the-organic-uplift-multiplier-in-app-marketing-separating-fact-from-fiction/

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In gaming, organic tends to meaningfully under-monetize relative to paid. And then with UAC / VO / AEO installs, I think organic generally (across verticals) under-monetizes relative to paid.

Answer 2

If you wanted to be more aggressive and there is a correlation between paid and organic installs, you can attribute the slope increase that you get in organic for every paid install. For example if the organic install and paid install relationship is linear:

Y = Mx + B, where x is the paid installs and Y is organic

You can use the slope M as a % contribution of organic LTV.

Need to remember in your query to exclude a couple of things:

• Don't count organics during a feature period
• Short time frame, since over a long period of time since organics should dominate
• Don't count installs from some kind of bursting effects
• Need to somehow account for potential chart position 
• Need to make sure that the segment youre correlating has the same underlying properties to eliminate heteroscedasticity

Comments

My question was more about what YOUR best practice / rule of thought is. Do YOU take organic revenue into account when measuring the performance of your UA campagins?

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I worked with people on this method yes. For example if M = .2 then for every paid install I will attribute 20% of organic LTV to that cohorts paid LTV. Again this assumes a correlation that you can tolerate and is just a rough estimate if you want to get more aggressive.

This also assumes that B is the consistent organic installs that are delivered when there are zero paid installs happening.

Answer 3

I think philisophically you have to decide how much of a role paid marketing plays in your product's organic magnetism. If you think all traffic would drop to 0 on a long enough timeline if paid marketing campaigns were shut off, then I think it's worth including revenue from organics into your paid acquisition ROAS calculations -- there'd be no organic without paid. More on that in this answer: How can I measure the impact of brand marketing campaigns on my product?

I see developers get into trouble when they drastically change their marketing budgets and project forward assumptions that don't materialize about how organic growth will change. If you have a measured / observed virality coefficient, I don't think it's fair to assume that it grows larger when spend increases; it could just as easily go down as go up, especially if your baseline spend is quite high. I've seen developers build models that bake in assumptions about how organic installs will increase at a ratio greater than the increase in their spend just because they need that organic revenue in their ROAS calculations in order to break even on the increased spend. I tend to be conservative when projecting organic ratio growth against spend growth.