How To Effectively Monetize Your App or Game with Andres Prilloltensky, VP Marketing & Sales, Simpool

Q: So Andres, how should monetization managers plan their monthly attribution plan?

Andres: Monetization in games works like a live organism. It breaths. The internal games mechanics and live ops activities create THE NEED. Either by all king of progression mechanics which push the user towards advanced content, challenges, and achievements.

Considering that usage and purchases habits are also driven by seasonality ( weekdays, paydays, etc.) its always a challenge to make a plan, which will be flexible in one hand and easy to respond to, but also foresee the upcoming events and trends and will compile it into attractive offering and boost engagement.

Collecting the correct data will support this and provide meaningful insights on customers' habits, most common monetization points, and triggers and utilize them to create the relevant OPPORTUNITY.

Q: How can you effectively optimize your data for your users?

Andres: Well, data shows that one size DOESN'T fit all. Users are different personas; hence, they have different engagement and purchase habits. When we approach a customer with an offering( either active or proactive), we must compile past purchase patterns, demographic characteristics, and engagement levels.

High engage users aren't necessarily part of the high purchaser's group.
Many companies rely solely on purchase patterns, but it is important to correlate them to their needs. As mentioned previously, as I see it, it starts with a proper analytical layer, which can segment users based on relevant parameters and anticipate the user's reaction to different offers.

Q: Which data points are the most critical to follow paying users

Answer: Data can be utilized in 2 ways - current state and historical Progression. It provides two different insights:

1. Current state - to approach and offer users relevant content, which matches its purchase habits, previous purchases( both price and content).

2. Historical Progression - it provides insights on what brought the users to this point, what triggered it to pay, time passed for the first purchase and in between followed purchases, how does it correlate to seasonality.

Also, demographic attributes( country, devices, and media campaign) are strong indicators and predictors of the next activity.

Q: What are the major challenges you people are facing when trying to optimize?

Andres: Since so many aspects can be optimized, there is always a challenge to decide what would be the next test in the pipe. Also, since there are few strict rules on how to run a valid test, companies tend to run invalid AB testing in many cases, which is a pure waste of time and money. In https://simpool.io/, we are building the next generation of optimization, which we call optimization on steroids :-) it is based on the largest data sandbox where companies can run an unlimited amount of what-if scenarios and basically spare most of the 'pains' mentioned in this article.