Eric Seufert’s Post

Measuring marginal organic contribution from paid marketing One trap that mobile-first companies often fall into is believing that organic installs are the result of totally undirected, spontaneous, aimless discovery. This is a trap because it's unlikely; it's rare for a truly static, stable baseline of organic installs to exist for a company independent of paid marketing. Organic baselines can be tested. The most brute-force approach to establishing an organic baseline is to shut off paid marketing completely. But shutting off marketing spend across the board isn't practical for most companies, which intuitively understand that paid marketing is their primary source of revenue generation and thus can't afford to stop marketing just to test an organic baseline. 

Optimizing growth: the “leaky bucket” isn’t an early-stage retention problem Product managers and data analysts tend to focus on optimizing the user onboarding funnel, or FTUE, more than other segments of the user lifecycle. As tempting as it is for a product team to focus a disproportionate amount of its energy on optimizing the onboarding funnel, ignoring the elder period of the user timeline is a mistake. In reality, user churn is more expensive later-stage than during the onboarding process: a user who has been in a product for a year is, by definition, more engaged than one who just joined. Losing the user with a year of tenure is more damaging to the business than losing the early-stage user because of that proven affinity and acquired behavioral data.

I’m looking forward to this!

Can mobile ad networks succeed beyond gaming? A recurring objective for mobile gaming advertising networks has been to expand to non-gaming clients. The allure is obvious: broadening the scope of both supply (advertising inventory) and demand (bids on inventory) beyond gaming could materially grow the revenue opportunity for these companies. A valid question to ask in considering the viability of a mobile gaming network expanding to non-gaming verticals is why it hasn’t happened at an appreciable scale yet. I believe three peculiarities of the mobile gaming advertising market — reliance on context for targeting, the ability for non-paying users to nonetheless be engaged, and the diversified strata of genres with mutual appeal — are clarifying when considering why mobile gaming advertising networks haven’t seen significant traction with non-gaming advertisers or publishers.

Brand Equity on Mobile Brand recognition isn’t the same as brand equity; brand recognition can decrease a firm’s marketing costs, but it can’t eliminate them completely on mobile, and it also doesn’t directly influence revenues (as a result of consumer response) as it does with retail goods. Because of the nonexistent switching costs between apps, the lack of information gaps (users can immediately understand the quality of an app for free) and the resultant lack of brand loyalty, and the opacity of mobile as an ecosystem, brand recognition may award a developer a marketing advantage, but it doesn’t necessarily produce brand equity.

It’s time to retire the LTV metric For many mobile advertisers, the LTV / CAC ratio sits at the very heart of commercial operations — LTV / CAC is the fundamental measurement of product viability, encapsulating both marketing efficiency and product monetization. But the LTV metric is an anachronism on mobile. For one, no one thinks about monetization on the basis of some abstract “lifetime”: in this second act of the mobile economy, users are sticky, products are enduring, and monetization streams are complex. Rather, marketers should approach growth from the opposite perspective: what is the optimal way to structure cash flows to support the growth of the business?

I think a good indication of Apple's intention to comply with the DMA is that it has rejected Epic's alternative app marketplace submissions over similarities in button sizes and colors.

Netflix Games: mistakes and opportunities Netflix seems to be employing the same tactic with games that it does with streaming video, which is to aggregate a large pool of filler content that isn’t distinguished artistically or critically yet provides subscribers with ample opportunities to engage with the service. This ignores the qualitative differences between streaming video and games: video can be consumed passively, whereas mobile gaming demands active engagement. Games can’t attract engagement by being just good enough; there simply exists too much costless competition in mobile games to build an audience that way. Whereas streaming users are locked into their subscription services for at least a month, mobile gamers face no content switching costs. There is no viable “volume play” in a mobile gaming aggregation strategy.

The emerging marketing economist The use of any econometric, or probabilistic, model to map inputs (marketing spend) to outputs (conversions) requires something of a dual workflow: determining the commercial effects produced through different channels to allocate budget, and then actually managing campaign performance at the level of an individual channel to ensure that budget allocated there is used most efficiently. These workflows don’t operate on the same cadence: cross-channel econometric models are generally updated monthly or quarterly in order to smooth effects and capture as much meaningful data as possible, whereas campaign optimizations — for instance, creative adoption and budget allocation decisions across campaigns within a channel — tend to happen at least once per week, if not more.

Meta’s “pay or okay” model violates the DMA The EC's determination in the case of Meta's use of "pay or okay" -- that a third, suboptimally-monetized version of the service be offered if advertising and subscriptions are the monetization mechanics chosen to support the business -- imposes the requirement that the gatekeeper offer an access option to consumers that is less economically valuable to it than the others, and which may not justify offering the service at all.