User Acquisition Analytics

Main criteria for optimization is Predictive ROI:

Predictive LTV is a model driven calculation that would be based on historical data from the existing products and unit economics’ benchmarks for a new game focusing on Daily Retention and ARPDAU; where model would track Day 1,3,7,14,28 LTVs and compare the trajectory against delta of predicted final LTV numbers.

The model will be adjusting itself by comparing predicted LTVs with the actual ones. The optimization can be based on:

CPA Optimization:

  1. Try not to narrow down the attribution window for a targeted action/event
  2. Use proxies. Proxy is the event happening prior the main event & indicating high chance of the main event completion.
  3. Longer lifetime leads to lower accuracy LTV predictions.
  4. It may take months to nail down LTV for midcore/hardcore games.

CPI Optimization:

  1. CPI optimization is widely used for Hyper Casual games.
  2. Moreover, due to the genre specifics, CPI is used by many as the main criteria for deciding on the game’s future.
  3. In other words, for an unfinished hyper casual title it is ad CPI that tells if it’s worth continuing the product

Ideally, the campaign optimization decision should be made 24 hours after install. Purchasing traffic with broader targeting at launch: the narrow targeting data might be misleading during the scale up stage. The higher the bid is, the more inventory is available. Inventory = channels + audience. It’s not a linear function though.

In a normal UA Lifecycle UA campaigns are performing their best at the hard launch stage. It becomes challenging to scale up profitably at the maturity stage of a product lifecycle. Updates are giving the second life to a product resulting in improved ROAS.

Creative: Brief, delivery, optimization.

Creative is at the top of the conversion funnel pursuing the goal to drive best possible conversion rates through high frequency of content delivery, ongoing A/B tests & iterative optimization.