17.03.2023

Principles of monetization in Belka Games. Funnel, payments, ideas

The second material by Evgeny Gilmanov, head of monetization at Belka Games, is about the principles that guide the development and implementation of a monetization strategy in the company.

Evgeny Gilmanov, Head of monetization at Belka Games

In the first article, we talked about key metrics, monitoring, talked about how intersections with different departments of the company help to better understand the market situation and how to achieve greater efficiency from monetization due to this. In this one, we’ll talk about how to set up monetization on a project, as well as how to search and generate ideas.

Set up your monetization

Give the opportunity to pay

It doesn’t matter what stage of life your project is at. It is important that potential paying players have the opportunity to pay.

By default, there should be a bank in modern mobile freeplay games. Even with 5-6 lots of hard currency: this is enough.

Think about user behavior: how and when the player will meet with a purchase, why he will want to buy something. It is not necessary to throw popups at the player from the start, but at the right moment (in puzzle games this is usually the end of moves or lives) it is worth bringing the user to the bank or offer and offering him to buy what he needs.

Build a funnel of the first purchase

First, build immersion funnels into your product (First Time User Experience). The player must understand how the game works, how to win, what is the main game cycle. And then you can work out the payment funnel — tell the player how the payment will help him, how much this advantage will be enough for him, what emotions he will receive after the payment. For example, it can be a very strong character, a set of boosters for completing levels, or unlimited attempts to complete levels for a while.

Show the player:

  • where can he pay;
  • what can he buy;
  • what will the purchased entities give him;
  • how long will the positive emotions from the payment last.

Give the player a tangible benefit from the first payment so that he gets good emotions after the purchase. For example, a player is faced with a lack of energy needed to pass any location in the game. Give him the opportunity to close this gestalt after the first payment. On the one hand, you will receive a payment, on the other, the player will receive an important emotion and feedback from the money spent.

The lowest conversion from payment N to payment N+1 is the conversion to the first payment, the path from zero to one. It is also the most important in the framework of payment behavior, because the more payments a player makes, the more likely he will pay again.

Another important fact: paying players are much more likely to return to the game. To verify this statement, ask your analyst to divide new players into cohorts of those who paid in the first 3 days and those who did not pay, and compare the rate of return to the game for a longer period. The result will show how important the difference between the paying and non-paying audience is in your game.

It is very important to push the player to the first payment — and the sooner, the better.

Another issue is much more complicated, and we ourselves have to work with this in the framework of our projects. It sounds like this: how to encourage players to start spending hard currency. And this question needs to be considered even earlier than the conversion to the first purchase.

A common practice of free—play games is to give the player a certain amount of hard currency from the start. Some go further, and as part of hard-onboarding, they guide the player through spending hard currency on various bonuses and other elements that simplify the game.

Others do not stop there either, and regularly issue hard currency for achievements in the game.

All these are ways to set up a player’s connection between spending hard currency and getting dopamine. When the currency runs out, the player has a logical need to get the advantages that it gave again.

On the other hand, during gaming practice, users have time to develop their habits, and it will not work to change them by simple methods. If a player is used to saving in other games, he will continue to save in your game, and will postpone the moment of spending an important rare resource until the last.

Study recurring payments

When you gain a base of paying players, constantly study it. Give players more incentives to pay through additional gaming activities and moderately favorable offers. The measure here is a relative concept, and depends on the balance between the desire to make a payment and the impact on the balance. In our practice, there is a term “hangover” — when, after large discount promotions, the paying audience is saturated and the average revenue temporarily decreases.

Discount promotions allow you to raise revenue per payer, move the player to a higher cohort by the average payment and the amount of payments. But do not forget that every promotion and discount is a decrease in the value of what you are selling. So you risk developing the habit of buying only discounted offers from the player.

Risk is not a problem, but an opportunity. Many games initially put inflated hard currency prices in order to maximize the share of trigger purchases through the offer system. It is your right to decide how purchases will be distributed in your game. The main thing is that with all this, the product margin grows in the long term.

When we talk about repeat payments, it is worth mentioning a very interesting segment of the audience. These are active players who paid in the previous period, but stopped. They are still with you and already know about the benefits of payments, so be sure to work with them regularly: find out how many such players you have and try to get them back to payments.

How do I get them back? An offer with a bigger discount than usual, an exclusive gift, additional gamification: make a payment, and you will receive additional bonuses for several days. It all depends on the possibilities of the game and your imagination.

Segment the players

If your product has been on the market for several years, it has certainly gained a large-scale and diverse player base. They will differ in many ways: demographics, payment behavior, payment sizes, the amount of payments for a lifetime in the game, preferences for features — you can list for a long time.

It is useful to identify user indicators for yourself and segment players so that different users receive offers with different costs and benefits.

Cohortization helps to adjust the balance of monetization and gaming features, assess the impact of features on the structure of the paying audience, investigate the dynamics of cohorts over long time periods, and so on.

It is worth mentioning here the fairly common terminology of whales, dolphins and fry. Quite a lot of materials have been written about it, here is one, for example.

You can segment the database in different ways: someone starts from the amount of payments during their stay in the game, someone – in the period of the last days, and someone simply divides the monthly revenue by percentages and receives segments based on them.

We have studied a number of practices and approaches and have done so:

  1. We structured the revenue and the payers for several months according to the amount of payments.
  2. Divided into fractions. N% of players bring M% of revenue.
  3. The ranges of amounts for the period were revealed in these shares.
  4. We have fixed the ranges of payment amounts for 30 days and are already working with this knowledge.

It is important to monitor the balance of these cohorts here. There is no perfect balance: they all have their own risks and peculiarities, and suggest different ways of developing monetization and marketing strategies.

Examples

  1. 80% of your project’s revenue is concentrated in 0.5% of paying players who give $500 on average every month. On the one hand, it’s great, you know how to attract and save whales, on the other hand, the product is financially very dependent on a small group of paying players. An unsuccessful update can alienate these players, which will pose great risks to the business.
  2. Another picture. You have quite a lot of payers and the revenue from them is balanced. This model is well protected from the risks of the previous paragraph, but it is worth asking yourself the question, why did this happen? Where are those whales, can my product provide an opportunity to pay really a lot?
  3. The third picture. All revenue is made by players who pay conditionally minimum payments. There are many of them, and the income for each is small. The following questions arise here. Why don’t they make higher payments? Why don’t they pay a lot on a long stretch? How to increase the income and receipt of your paying audience?

You can also write a lot about working with whales, but below I will give a vivid case that we encountered just recently.

Another example

There are two players with the amount of payments of $300 for the last month. We refer them to whales. But if you look at the players in detail, you can see that player A made five payments of $ 100 dollars, and player B made 100 payments of $5.

Everything would be fine, but depending on the size of the payment, players receive different benefits. Here you can start asking questions:

  • which of these players do we give the most benefit to?
  • why can one of the players receive more profitable offers?
  • do we want the player to receive favorable offers if he is already inclined to pay?

This case prompted us to experiment with additional segmentation not only by the amount of payments, but also by the payment behavior within the period under review.

Ideas

As I wrote in the first article, if you are just starting to implement monetization in a product, you should not reinvent the wheel and come up with creative mechanics where the base is not implemented. But if you have already prepared the database and configured the user paths before the payment, then it’s time to think about experiments.

I have developed one principle for myself: the main thing is to get an idea.

In order to systematize the search and not lose ideas, we keep personal backlogs, tasks from which we periodically discuss and take to work.

Where to get ideas from

Our main sources of information:

1) External market data sources

  • Data.ai
  • GameRefinery
  • Playliner
  • Sensor Tower and others.

2) Profile reports are freely available

Here I can recommend analytical reports from Newzoo, Gamesindustry.biz, LoopMe. It is also useful to look at devtodev — they publish the most important reports every month.

3) Feature articles on game design, monetization and game analytics

4) An expert group within the company

People who are closely involved in the industry not only from the development side, but also from the side of an ordinary player. They can play and thoughtfully analyze games from the side of game design, monetization, narrative, and so on.

5) Study of top games of new markets for you (for example, Asian)

Games from the local top are radically different from what we usually see on phones in North America and Western Europe. The wider your view, the more ground there is for creativity and experimentation.

6) The surrounding world

Do not limit yourself to the world of mobile games. 1+1 promotions or discounts when buying two products of the same brand in cosmetics and clothing stores, offers for regular customers in grocery supermarkets, seasonal and holiday sales — some of this can form the basis of your offer or bundle.

7) The team’s knowledge base over the past few years

Everything new is well—forgotten old, and what didn’t work a couple of years ago may well show good results after a while or form the basis of a new idea.

How to take ideas

Well, we gathered a lot of knowledge and studied a lot of solutions on the market. What to do with it next? The first thought (very tempting) is to copy and paste without unnecessary questions. But there are pitfalls of reality waiting for you along the way. Let’s go through the chain of arguments against copying features 1 in 1:

  1. Any change in the product is caused by its own reasons — and you are unlikely to guess about them. What was the state of the reference product when the feature was introduced, and what is the state of your current product?
  2. Most likely, you will encounter segmentation. You can buy the same bundle with different benefits. If you do not take this into account, you will most likely calculate the balance incorrectly.
  3. Your audience is not a competitor’s audience. A competitor’s well-functioning mechanics may simply not suit the setting and presentation of your audience.
  4. To implement a new idea well into your project, try to understand it as deeply as possible and adapt it to your needs.

Answer your questions:

  • Why does the idea you like work in the project you have reviewed?
  • How is the feature related to the rest of the features in the game and how does it work for the user?
  • If you have such functionality, then who in your game will it be designed for?
  • How to fit ideas into your game as narratively and smoothly as possible?

This will help you get rid of potentially unnecessary features and make the user experience optimal during implementation.

How to prioritize ideas

We use the “Calculation from above” method — that is, we answer a number of questions:

  1. How much feature or feature change can give the maximum potential profit?
  2. How many players will interact with the features?
  3. What are the target metrics of the feature?
  4. Due to what will the growth of target metrics occur?
  5. How confident are we that growth will actually happen?
  6. What labor costs will be required to implement the feature?

Using this approach, you can understand how much a feature can give a profit in the best scenario. The basis of this technique is taken — ICE score.

In calculating the potential of the feature, we cut off the excess. For example, if it is turned on from the seventh day of life in the game, then we exclude newcomers from the assessment and take only the metrics of players who have lived in the game for more than seven days.

If the feature is designed to increase activity, then it is worth excluding inactive players from the potential audience — statistically, the entire cash register of activity growth is done by those involved.

If this is a monetization feature — for example, a new offer — then it is worth dividing the audience into cohorts of paying and non-paying, the effect on the cohorts will be different. Think about how you will segment offers, what the balance will be, what conversion rate each cohort has to existing offers, and how you can potentially touch other purchase items.

The estimate always has an error, and the resulting effect is likely to be lower. But the calculation from above will allow, on the one hand, to see all the shortcomings of the feature under a magnifying glass, on the other — to see its potential, which will raise its priority relative to others.

Many of our ideas go to the table after such an assessment, because they will not potentially benefit the product, or the labor costs outweigh the profit from implementation. The business needs the team to be engaged in the most profitable business in terms of its growth.

How to test ideas

The main tool, and I will not reveal anything new here, is A/B tests.

No solution without a test test will give you growth with 100% probability, and in some cases it can also have a negative impact — and you may not notice it with a simple rollout on the prod. Don’t take other people’s hypotheses for granted. Even if the producer of the game really likes them, they work well with competitors and you have a reliable insider.

All hypotheses remain hypotheses before being tested by the test.

Any monetization feature after a positive meaningful test needs to confirm the results for the entire audience of the game. It is also good to lay at least two or three iterations to get the optimal result, because after the first launch you will have data on the use of the feature.

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