Building a traffic composition strategy on mobile | Mobile Dev Memo

Building a traffic composition strategy on mobile

In my recently-completed workshop series, Modern Mobile Marketing at Scale, I presented one slide which identifies and categorizes what I believe to be the most important traffic acquisition sources on mobile:

Certainly reasonable people might disagree on the tier distinctions made here, and I’m confident that other traffic sources could conceivably be included, but my belief is that the above channels, in aggregate, represent the vast majority of spend for most large mobile advertisers.

With such an extensive list of channels, an advertiser in the process of scaling their paid growth campaigns might ask themselves: where should I start? And how might the mix of channels change as overall monthly acquisition spend grows to $500k, and then to $1MM, and then to $10MM?

At very large levels of spend, an advertiser might use all of these channels. But as I point out in Opportunity cost and diminishing returns in mobile user acquisition, it is important for an advertiser to consider how channel diversification contributes to an overall mobile marketing strategy. Many — perhaps most — app advertisers could utilize Facebook exclusively for traffic acquisition, satisfy their growth goals, and not need to think about onboarding new channels in the short or medium term. But every advertiser hopes to scale spend to the utmost extent, and so at some point diversification is necessary. How does an advertiser know when they have reached that point?

There are certain strategic concerns that go into this decision. For example, how dependent does that advertiser want to be on Facebook, which is subject to potentially more pronounced swings in CPM prices during the Q4 holiday season, and which tends to require heavy investment into creative asset production as event-based campaign strategies like AEO and VO reach saturation. Similarly, a gaming advertiser might choose to focus on programmatic advertising at an early stage if they perceive their acquisition data to be co-opted when sent to an ad network; or they might believe that their app’s general use case is best communicated on a specific self-attributing network, like Snapchat or Pinterest for specific audience segments or Google for intent-oriented products like travel.

Another concern is team size and distribution of resources. For companies dedicated to staying lean and flexible with respect to headcount, it might make sense to use some ROI standard to focus spend on just a small handful of channels, exploiting the largest to the greatest possible extent while maintaining ROI and then moving budget to the second largest, and so on. I call this strategy the “Waterfall Budgeting Method” and it plays into the general rule that ROI and spend on a given channel are inversely correlated (ROI tends to decrease when spend on that channel increases). Since this is the case, an advertiser might pick the channel with the greatest spend potential, spend as much as they can on it until ROI descends to a target rate, and then hold spend steady there for the month and shift remaining budget to the next-largest channels under the same logic.

The opposite approach to the Waterfall Budgeting Method is what I call the “Distributed Budgeting Method”: the advertiser splits budget across as many channels as possible in order to maximize total portfolio ROI (since spend is minimized at the channel level, ROI can potentially be maximized). This budgeting strategy necessarily requires a larger team and thus tends to make economic sense at very large levels of spend (since the overhead of additional marketing staff must be outweighed by ROI improvements across the portfolio).

It’s common to see marketing teams that believe that diversification is de facto optimal and that operating across more channels is always cheaper and less risky than concentrating budget in just a few. This simply isn’t the case: often, in my experience, these teams end up onboarding small, immaterial channels, investing significant time into optimizing them and not exploiting their biggest opportunities as a result (see The “Quality vs. Volume” fallacy in mobile user acquisition for more on this subject). Teams need to consider their traffic composition thoughtfully — and, most importantly, they need to re-consider it regularly, evaluating whether they are most prudently deploying their advertising budget given the age, reach, and nature of their app.

Photo by Robert Lukeman on Unsplash