Can attribution modelling dispel the darkness in a post-IDFA world? When we had IDFAs and deterministic attribution, this sort of estimation based modeling was not necessary. However, as it is curtains on IDFAs, attribution modelling could be a way to retain marketing metrics like LTV and ROAS. How is this possible? Will it be accurate?We find out in our conversation with Chris Farm today, co-founder and CEO of Tenjin, in which we talk about what data we do have at our disposal, and how to make the most of it to build attribution models - from simple spreadsheet ones to more sophisticated ones. KEY HIGHLIGHTS🏃‍♀️ How attribution has shifted to Apple🧐 The gaps in ROI metrics for developers⚙️ How attribution modelling works📥 The inputs of an attribution model and the downstream metrics they impact💭 Let’s not forget the IDFV💪 The IDFV is more powerful that you would expect🤼 Signal-based vs deterministic🌱 How to start with a simple model and then refine with layered variables🚗 The drivers of model accuracy and inaccuracy🎯 We need to change how we define accuracy 🙋 Last-click is just one possible model 🔍 It is possible to create models without postbacks💡 How to work with aggregate data for good decision-making🏝️ Why attribution modeling is unnecessary when running a single channel 🕹️ Attribution modelling is especially suited to gaming companies ⚖️ The difference between attribution modeling and last-touch🦄 Why true multi-touch still doesn’t exist📝 How to create a V1 model in Excel🦸 Developers will rise to the challengeCheck out the show notes here: https://mobileuseracquisitionshow.com/episode/the-power-of-attribution-modeling-to-calculate-ltvs-in-a-post-idfa-world-with-chris-farm-co-founder-and-ceo-at-tenjin/**Get more mobile user acquisition goodies here:http://RocketShipHQ.comhttp://RocketShipHQ.com/blog**Check out our podcast featuring inside stories of how technology evolves and grows:http://HowThingsGrow.co

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