ABOUT ROCKETSHIP HQ: Website | LinkedIn  | Twitter | YouTube

KEY HIGHLIGHTS

🙅‍♂️ There is no such thing as ‘user lifetime’.

📈 LTV is often projected and estimated.

🤼 Different teams calculate LTV differently.

🤔 The traditional LTV modeling paradigm also assumes that the last-click paradigm is accurate, which may not be strictly true.

🤝 The LTV model that prevails is often a function of corporate politics.

FULL TRANSCRIPT BELOW

With much of our marketing decisions having been made around the LTV/CPI ratios, something that often many marketers forget is that LTV is a made-up number.

In an article on MobileDevMemo, Eric Seufert argued that the LTV metric is only partially useful to modern mobile marketers.

As Eric says: “there is no “user lifetime”, at least not in a way that can practically be applied to marketing operations.”

While it’s important to note that LTV is projected (and therefore is an estimate), what’s also worth noting is that there can be significant subjectivity in LTV calculations as a result of internal corporate political dynamics, especially in companies managing portfolios of multiple apps. (Yes, you could calculate your actual d365 LTV – but that will often come with a 365 day lag – and can often be too late for any effective decisioning).

For folks that lament the death of the LTV as a result of iOS 14 and IDFA deprecation, it’s worth noting, LTV was a veneer in the first place.

I’ve seen companies where different teams calculated LTVs differently – and this was the basis of significant political turf battles when it came to fighting for internal resources – both financial and headcount. These are just some of the contentious questions that I’ve seen: –     

-> How do we compare LTV or the payback period for an app in our portfolio with front-loaded monetization vs. one with long-tail monetization?

-> Should we use a longer payback period if an app has strong long-tail retention – and if most of its revenues come after year 1?

-> Which statistical model should we use? Should we use conservative or aggressive estimates in our models?

-> Should newer & unproven games get bigger ‘launch budgets’ until they prove their metrics?

-> Should we allocate disproportionate budgets to a game that is wildly profitable from its legacy users but has low LTV from new users?

-> Should we use a liberal or strict LTV/CPI approach (or in other words, should we discount the target ROAS numbers for games that have strong organics)? How much of organics should we attribute to paid installs?

-> Should we have a more liberal ROAS model if we have a wildly viral game?

-> Should we hit our quarterly profitability numbers – or sacrifice some of it for longer-term growth?

This is all assuming that a last-click paradigm is even accurate – which in a world where SANs oftentimes seem to capture excessive impressions and clicks so as to capture attributions for themselves, begins to appear increasingly problematic.

All these questions have a lot of subjectivity involved – and there is no one ‘right’ answer to the above. While in an ideal world these decisions would be made strategically with the goal of maximizing the company’s long term growth in mind, the reality often tends to be far more complex – especially since long term growth can mean different things to different stakeholders in a company. 

Oftentimes the LTV calculation that prevails comes down to who plays corporate politics better, especially in an established company with multiple teams competing for resources. Oftentimes this can come down to which VP/GM/business head is more articulate and/or has more allies within a company’s resource-allocation hierarchy. 

To some extent, this subjectivity and conflict is unavoidable when each VP/GM/business head is incentivized to grow their business unit(s) – and the CFOs/CEOs often don’t have full context on the nuances of each business unit’s operations.

It’s worth keeping in mind that while LTV had utility as a marketing metric, oftentimes the reality is never as clear-cut as a financial model can make it to be like. 

Yes, the LTV as a metric might die with the advent of iOS 14 and IDFA deprecation – but it was at best an imperfect metric to begin with. 

A REQUEST BEFORE YOU GO

I have a very important favor to ask, which as those of you who know me know I don’t do often. If you get any pleasure or inspiration from this episode, could you PLEASE leave a review on your favorite podcasting platform – be it iTunes, Overcast, Spotify or wherever you get your podcast fix. This podcast is very much a labor of love – and each episode takes many many hours to put together. When you write a review, it will not only be a great deal of encouragement to us, but it will also support getting the word out about the Mobile User Acquisition Show.

Constructive criticism and suggestions for improvement are welcome, whether on podcasting platforms – or by email to shamanth at rocketshiphq.com. We read all reviews & I want to make this podcast better.

Thank you – and I look forward to seeing you with the next episode!