Microtransactions as a form monetization in online free-to-play games

The first microtransaction and types of in-game purchases in DOTA 2. The encouragement of players for microtransactions in DOTA 2 and Counter Strike. How microtransactions are processing in DOTA 2 and Counter Strike: Global Offensive. Data description.

Рубрика Менеджмент и трудовые отношения
Вид дипломная работа
Язык английский
Дата добавления 17.07.2020
Размер файла 3,5 M

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Table 8

Great Sage's Reckoning

Day

Price of sold item, $

Quantity of sold item

Amount of sold items in $

DOTA 2 fee

April 28

24. 48

26

636. 48

63. 65

April 29

24. 32

21

510. 65

51. 06

April 30

24. 89

23

572. 47

57. 25

May 1

24. 60

25

615. 00

61. 50

May 2

24. 05

29

697. 45

69. 75

May 3

24. 65

27

665. 55

66. 56

May 4

24. 41

23

561. 43

56. 14

174

4259. 03

425. 90

According to results of the table, it is seen that the monetization from this item was the lowest one among all 3 in-game items with the rarity of “Arcana”. DOTA 2 fee from trades of this item was half as much comparing to “The Magus Cypher” and even lower comparing to “Manifold Paradox”. Nevertheless, the revenue of 425 dollars was generated in the period of 1 week only from trading of this item.

On the other hand, cases within another researched free-to-play online game Counter Strike: Global Offensive are needed to be researched by the same analysis with the visual presentation of results. Thus, the first case that will be reviewed by using the same analysis is “Glove case” and the visual chart will be constructed to see the fluctuation of prices for this item.

Figure 7. The Glove case's data

The table 5 shows data about “Glove case” about the average price per day pf sold day and the overall quantity of sold items.

Table 9

The glove case's data

Day

Price of sold item, $

Quantity of sold item

Amount of sold items in $

Counter Strike fee

April 28

0. 149

46655

6951. 60

695. 16

April 29

0. 149

49887

7433. 16

743. 32

April 30

0. 144

49277

7095. 89

709. 59

May 1

0. 146

50127

7318. 54

731. 85

May 2

0. 144

44320

6382. 08

638. 21

May 3

0. 151

43240

6529. 24

652. 92

May 4

0. 154

46653

7184. 56

718. 46

330159

48895. 07

4889. 51

The difference is seen between cases in Counter Strike: Global Offensive and “Arcana” items in DOTA 2. According to the figure and to the table 5, “glove case” have low average price - about 0.148 dollars, but because of this fact cases are selling itself in much greater amounts, the quantity of sold “glove cases” used to reach 50 thousand on the May 1 and the monetization from the trade of this item was 730 dollars what is nearly double as much comparing to “The Magus Cypher” item from DOTA 2. The method that Counter Strike uses is working super effectively in the case of “glove case” at least.

The other case that will be analyzed is “Spectrum case” as it was mentioned in previous sections.

Figure 8. The spectrum case's data

As it seen from the figure, “spectrum case” has medium fluctuation with the lowest price point of 0.134 and the highest price point of 0.147. Quantity of sold items does not depend of the price of the item, probable, because of the fact that price is decently low comparing to other in-game items such as skins for in-game weapons.

Table 10

The spectrum case's data

Day

Price of sold item, $

Quantity of sold item

Amount of sold items in $

Counter Strike fee

April 28

0. 136

47254

6426. 54

642. 65

April 29

0. 141

50050

7057. 05

705. 71

April 30

0. 136

49520

6734. 72

673. 47

May 1

0. 134

51244

6866. 70

686. 67

May 2

0. 138

57322

7910. 44

791. 04

May 3

0. 144

48270

6950. 88

695. 09

May 4

0. 147

53876

7919. 77

791. 98

330159

49866. 10

4986. 61

Table 6 shows results of data collected from spectrum case on the Steam market in the period of one week. It is seen that even that the average price of this case is lower comparing to the “glove case” - about 0.139 dollars versus 0.148 dollars in the case of “glove case”, the “spectrum case” had higher monetization than “glove case” - about 4986 dollars of pure fee went to Counter Strike from trades of this item in the period of 1 week.

The final case that will be researched is the “Danger Zone case”

Figure 9. The Danger Zone case's data

The figure showed that fluctuation in price is medium, but the fluctuation in quantity of sold items is pretty high. The possible reason for the rapid decrease in amount of sold items between day 6 and day 7 in the researched week was a sharp increase in the average price of “Danger Zone case” and this is why players were reluctant to purchase this item.

Table 11

The danger zone case's data

Day

Price of sold item, $

Quantity of sold item

Amount of sold items in $

Counter Strike fee

April 28

0. 049

82340

4034. 66

403. 47

April 29

0. 050

86889

4344. 45

434. 45

April 30

0. 048

80010

3840. 48

384. 05

May 1

0. 045

84220

3789. 90

378. 99

May 2

0. 047

85039

3996. 83

399. 68

May 3

0. 045

83930

3776. 85

377. 69

May 4

0. 051

77210

3937. 71

393. 77

579638

27720. 88

2772. 09

Thus, the data from the table and the from the figure shows that the average price in the case of “Danger Zone case” is much lower comparing to other two previously described Counter Strike cases, however, amounf of sold “Danger Zone cases” is higher comparing to other two types of cases, but the monetization is half as much as it was in the analysis of “glove case” and “spectrum case”. Nevertheless, 2772 dollars of pure profit were generated during only the week of trades of this “free” item that players can randomly receive by playing the game.

The next point that will be analysed in terms of this work is the testing of third hypothesis about possible correlation of players online and number of sold items. The tools that will be used and data that is going to be collected used to be described in previous sections, therefore, only results of data will be shown here. The first item will be “Manifold Paradox” from DOTA 2 and two figures shows data for 2018 and 2019:

Figure 10. Manifold Paradox's trades and players online in 2018

Figure 11. Manifold Paradox's trades and players online in 2019

It is seen that according to the figures there is no strong correlation between these variables in the case of “Manifold Paradox”. However, in the 2019 in May there was a sharp increase in number of sold items, but the growth of players online was not that high. At the same time, in 2019 after the may amount of players online started to fall in numbers and the amount of sold items also started to drop, but in higher percentages comparing to players online. In 2018 fluctuation was not that high within number of sold items, however, in august there was a sharp increase in number of sold items and at the same time there was a growth in number of players online. Nevertheless, correlation has to be visually presented:

Figure 12. Correlation between players online and trades

Moreover, the correlation was calcuted in Excel with the help of such funstion as CORREL() and it was equal to 0.57 for the 2 years what means that the correlation is a slight positive correlation, however, the number in 0.57 does not give the opportunity to claim that there is a strong correlation between these variables. However, there is 2 more items with rarity of “Arcana” for which correlation will be calculated for the same period of time.

Therefore, the next item from DOTA 2 will be “Demon Eater” for such in-game character as Shadow Fiend. Once again figures will be constructed with the aim to visually represent collected data.

Figure 13. Demon Eater's trades and players online in 2018

Figure 14. Demon Eater's trades and players online in 2019

The figures show that the quantity of sold items is lower in average comparing to “Manifold Paradox”, but the same fluctuation is seen on the both figures. However, the highest point of players online does not match the highest point of sold items. The correlation once again has to be visually presented

Figure 15. Correlation between players online and trades

The correlation is positive once again, but it is not strong, therefore in the case of such in-game item as “Demon Eater” from DOTA 2 there is once again the slight correlation and according to the function from Excel, it equals to 0.639 what is higher comparing to “Manifold Paradox”, but still not high enough to claim that the correlation is strong betwenn such variables as players online and amount of sold items.

The final item from DOTA 2 that will be analysed is “The Great Sage's Reckoning” and for this item also the same tools of analysis will be used with the aim to find correlation.

Figure 16. The Great Sage's Reckoning's trades and players online in 2018

Figure 17. The Great Sage's Reckoning's trades and players online in 2019

Figures shows that may in both 2018 and 2019 was the month with the highest amount of sold items, however, it was not the highest month in terms of online, but online was pretty high within these months anyways. The noticeable difference in amount of sold items is also seen between 2018 and 2019. The reasons for this can be diverse: hero could become more popular in games, because of the fact that there was an in-game update that used to make this hero better or any other reason. Now the correlation itself has to be visually presented

Figure 18. Correlation between players online and trades

The figure of correlation shows that there is no correlation between such variables as players online and amount of sold items per month. Indeed, the calculation in Excel shows that the correlation equals to 0.145 what means that the number is close to the 0 and it results to the fact that in the case of “The Great Sage's Reckoning” there is no correlation and the researched variables do not depend on each other.

At the same time, with the aim to test the hypothesis the same analysis should be done for in-game items from Counter Strike: Global Offensive - for cases. Thus, the first case that will be analysed is the “Glove case” and for this item the visual figures will be constructed with the aim to visiually support to the results of collected data

Figure 19. Glove case's trades and players online in 2018

Figure 20. Glove case's trades and players online in 2019

The figures show that the fluctuation in amount of sold items was decent, but not super high. Moreover, it is seen that the the highest point of sold items and the players online used to happen in the same month for both figures what can tell about possible high positive correlation between researched variables. With the aim to test this theory, correlation is needed to be calculated and visually presented:

Figure 21. Correlation between players online and trades

According to the figure with correlation between such variables as players online and amount of sold items for “Glove case” the correlation is positive and pretty high, but with the aim to calculate the exact number it is needed to use Excel function as it was in the case of “Arcana” items from DOTA 2. Therefore, the correlation equals to 0.949 what means that the correlation eagers to the perfect correlation with number of +1. Thus, the correlation is positive and it is high for the “glove case”. Nevertheless, it is the first in-game item that has the positive and strong correlation from all researched items at this moment, other 2 items from Counter Strike: Global Offensive have to be analysed with the aim to test third hypothesis.

The other in-game item that will be analysed is the “Spectrum case”. The same analysis will be done for this in-game item from Counter Strike:

Figure 22. The spectrum case's trades and players online in 2018

Figure 23. The spectrum case's trades and players online in 2019

The figures show the minimal fluctuation in the the 2019 both in amount of sold items and number of players online and decent fluctuion in 2018 for both variables. However, the fluctuation is not so vividly represented and cannot be seen via these 2 figures, therefore, once again another figure with correlation will be construncted and the correlation will be calculated:

Figure 24. Correlation between players online and trades

It is seen that positive fluctiation is present, but it is not that high comparing to the previous “Glove case”. Indeed, the correlation in this case equals to 0.62 what means that the correlation is slight and this result is similar to the result of correlation of the “Demon Eater” from DOTA 2. At the same time it the third item from all analysed in-game items that have slight and positive correlation.

Finally, the last in-game item from Counter Strike that will be reviewed is the “Gamma 2” case. This case replaces “Danger Zone case” for the reasons that were described previously. Two figures that show changes in researched variables within a period of 2 years will be constructed first:

Figure 25. Gamma 2 case's trades and players online in 2018

Figure 26. Gamma 2 case's trades and players online in 2019

The fluctuation is not high for both variables in both 2018 and 2019. At the same time in 2019 the highest point of players online matches with the highest point of sold items what might mean that some sort of relationship exists between researched variables in the case of “Gamma 2” case. However, to be completely sure about this fact it is needed to present another figure with actual correlation between these variables and calculate the exact number of correlation:

Figure 27. Correlation between players online and trades

The correlation is positive and near to be the strong one. However, the exact number is needed to claim that there is a strong correlation between amount of players online and amount of sold items in the “Gamma 2” case. The calculations shows that correlation equals to 0.742. It means that correlation is definitely positive, nevertheless, it is not enough to be totally sure and claim that correlation is strong. Because of the fact that 0.742 < 0.8, then it is not enough to claim that in this case the strong correlation is seen. There is a correlation, but variables have medium relationship from each other and not strong one how it was in the case of “Glove case”where correlation was higher than 0.9.

Now it is needed to conduct an independent t - test analysis for both DOTA 2 and Counter Strike: Global Offensive. The researched data was mentioned in the previous sections, now it is time to conduct the analysis with the aim to test the hypothesis that there is no difference between means of two groups of variables. First of all the DOTA 2 data will be studied and tested by using independent t - test in SPSS. The results are following:

Table 12

T-test

Group Statistics

factors

N

Mean

Std. Deviation

Std. Error Mean

online

0

12

443668, 58

52498, 236

15154, 935

1

12

488684, 33

40745, 254

11762, 142

Therefore, it is seen that sample sizes are equal in the case of DOTA 2 (12 months had microtransaction within them and 12 of them did not). The mean is slightly higher for the second group with the factor “1” and this group of months where there was a microtransaction. Standard deviation and a standard error mean higher in the case of the first group. The other table provides more substantial results:

Table 13

Independent Samples Test

Levene's test for equality of variances

F

Sig.

online

Equal variances assumed

. 324

. 575

Equal variances are not assumed

The table provides the information about with the result of Levene's test for equality of variances and the major point on which the attention should be paid is the significance of the F value. It is needed to understand if variances are equal or have a significant difference. In the equal it is divided on: equal variances assumed and equal variances are not assumed what means that if they are assumed then it would be needed to work with the data from the first row and if they are not then it would be needed to work with the second row. In the case if significance is lower than p and p in this case equals to 0.05, then the variances or standard deviations are not the same and the whole test will be question after this point. However, the significance is higher than p value - 0. 575 > 0. 05 what is not statistically significant.

Table 14

Independent Samples Test

T - test for equality of means

t

df

Sig. (2 - tailed)

Mean difference

Std. error difference

online

Equal variances assumed

-2. 237

22

. 028

- 45 015. 750

19 183. 849

Equal variances are not assumed

-2. 237

20. 724

0. 029

- 45 015. 750

19 183. 849

The results of this table is playing a key role in testing a null hypothesis and understanding if there is a difference between researched mean of variables or not. Because of the fact that in the previous table it was stated that equal variances assumed then the data from the first row only will be analyzed. The column that provides the information about the means is the significance value once again and as it is needed to compare this value to the p value - 0.05 and in this case, it is seen that 0. 028 < 0. 05 what means that means are different and the null hypothesis is rejected for DOTA 2 only.

Now it is needed to do the same independent t - test analysis in SPSS for data collected from Counter Strike: Global Offensive online. The results for the first table are the following:

Table 15

T-test

Group Statistics

factors

N

Mean

Std. Deviation

Std. Error Mean

online

0

11

33 3596. 09

52 498. 236

15 154. 935

1

13

38 2318. 31

40 745. 254

12 480. 278

Once again, the mean is higher for the second group with the factor 1 what means that months which consisted of new offers of microtransaction had higher players online compare to other months. The sample sizes are slightly different - 11 months versus 13 months. Second table will provide more data and will help to see if there is a difference in the variances between researched groups of variables:

Table 16

Independent Samples Test

Levene's test for equality of variances

F

Sig.

online

Equal variances assumed

2. 217

. 151

Equal variances are not assumed

As it was in the case of DOTA 2, the significance is lower than p, because p equals to 0.05 and 0. 151 > 0. 05 what means that variances are not significantly different. At this point, the results are similar to the results of DOTA 2, however, the last part of the table is not analyzed yet. Therefore, the second part of the table has to be shown and analyzed in order to test the null hypothesis for Counter Strike: Global Offensive:

Table 17

Independent Samples Test

T - test for equality of means

t

df

Sig. (2 - tailed)

Mean difference

Std. error difference

online

Equal variances assumed

-2. 362

22

. 027

- 48 722. 217

20 629. 625

Equal variances are not assumed

-2. 317

19. 125

0. 032

- 48 722. 217

21 024. 196

Because of the fact that equal variances assumed then only the first row is going to be analyzed. Once again with the aim to test the null hypothesis which claim that there is no significant difference between researched groups of variables, the significance value has to be compared to the p value. It turns that 0. 027 < 0. 05 what means that there is a significant difference between means of groups of researched variables. The result is similar as it was in the case of DOTA 2 and the null hypothesis is rejected once again. Overall, null hypothesis completely rejected, because for both researched online free-to-play games, the means in players online between months when the new offer of microtransaction was present is higher comparing to the months when there was no new offer of microtransaction.

Now it is time to finally show results of both surveys that were conducted among Counter Strike: Global Offensive and DOTA 2 players and actual question that respondents were asked within both of these surveys are stated in Appendex 1 and Appendix 2. The first survey for which results will be shown is DOTA 2 survey. As it was stated previosly, it was needed to collect answers from 96 respondents who used to play DOTA 2 or still playing this free-to-play online game. Nevertheless, in fact, about 140 answers were collected what does not change the confidence level or confidence interval, but it is still better to study 140 answers of respondents and not only 96. First of all, at the very start of the test, the respondents were asked if they ever used to make an in-game purchase. 102 respondents said “Yes” while other 38 said “No” what means that within this survey the data from 102 respondents will be used for analysis of data about types of microtransactions in DOTA 2. Within second question respondents were asked about the annual waste of money from respondents and survey showed that from 102 DOTA 2 players who ever used to waste some real money on in-game items, the average annual “check” is about 5112.21 rubles what is pretty high monetization to the free-to-play game. However, this average annual check can not be representative, because some respondents might waste about 30 thousand rubles annually, while others are wasting only about 5 thousand. Such function as MEDIAN() shows that the the median number in the survey is 3000. It means that 50% of respondents waste less than 3000 and 50% waste more than 3000 rubles annually. This number is much lower comparing to the average annual “check” that was calcutated. The table with percentages of annual waste from respondents is needed to be constructed with the aim to analyze the data in more details.

Table 18

Intervals of annual “check”

Intervals of annual “check”

Number of respondents within the interval

Percentage

1 - 1000

14

13. 73 %

1001 - 1999

4

3. 92 %

2000 - 3500

40

39. 22 %

3501 - 5000

17

16. 67 %

5001 - 10000

18

16. 65 %

10 001- 15 000

3

2. 94 %

15 001 +

6

5. 88 %

102

100 %

The table shows that about 40% of respondents waste from 2000 to 3500 rubles annually while only about 6 percent of players waste more than 15 000 rubles. At the same time, nearly 14% of respondents have annual “check” lower than 1000 rubles what is still pretty high percentage within this sample - 14 respondents out of 102.

Another question on which respondents had to answer within this survey is the type of microtransaction on which they waste the most amount of mooney annually. The analysis of this question provides the results of SPSS table that focuses on the average for every type of microtransaction and other statistical indicators.Thus, according to the collected data from the survey, following results can be displayed:

Table 19

The monetization from different type of microtransaction in DOTA 2

Arcana

Treasures

Other items from the Steam

DOTA PLUS

“The International” battle pass

N

9

15

19

16

43

Mean

3522. 22

2196. 67

2163. 16

1675

5883. 49

Median

3200

2000

2000

1350

4500

Mode

2500

2000

2000

1000

5000

Std. Deviation

1082. 56

1212. 21

1248. 20

1011. 59

5965. 39

Minimum

2400

450

500

700

1000

Maximum

5000

4500

5000

4000

30 000

The table shows results of collected data for the third question (the type of microtransaction on which reposndents waste the most amount of real money annually) and results of collected data for the fourth question (how much respondents waste on the type of microtransaction that they used to chose in the previous question - it means that if respondend used to chose “Arcana” item in the 3rd question, he or she shoould state the annual “check” only for this specific type of microtransaction. It is seen that the most popular and at the same time the most profitable for DOTA 2 type of microtransaction is “The International” battle pass. The least profitable type of microtransaction is the DOTA PLUS and the least popular within players are “Arcana” items. There are several possible reasons for this, but they will be discussed in the next section of this work. Next questions within survey were considering more behavioral factors of respondents such as could new microtransaction motivate players or do reposndents ever felt like the game forces them to purchase some in-game item via real money and so on. Thus, the fifth question was about if respondents ever felt that the game itlsef forces them to pucrhase some in-game item. Survey showed that 42 respondents believe that game sometines definitely forces them to purchase some in-game items and perform the proccess of microtransaction. On the other hand, 60 respondents answered negatively on this question. Next question's thematic was considered how players used to perform such type of microtransactions as purchasing of “Arcana”- either through DOTA 2 market direclty or throgh Steam market. This question is needed with the aim to understand what percentage of players are purchasing “Arcana” derectly from the DOTA 2 store, because in this case, game has higher monetization from this type of microtransaction. The survey showed that 27 respondents out of 102 used to perform microtransaction exclusively through Steam market while 21 respondents are using only DOTA 2 market for performing microtransactions. 42 respondents used to buy “Arcana” items both through the DOTA 2 store and Steam market. Only 28 respondents stated that they never used to purchase any “Arcana” item. Within the final question in DOTA 2 survey respondents were asked if they are going to come back in the game if they would stop it for a while and a new microtransaction came out. The results showed that out of 102 respondendts who ever made a microtransaction 29 respondents are definitely would come back to the game with the aim to check out new microtransaction offer. 48 respondents were not so sure in the answer, but they stated that more likely that they would come back to the game with the aim to check new microtransaction. 18 players within survey stated that they most likely would not come back to the game, but they are not sure about this. Finally, 7 respondents would definitely not come back to the game because of some new microtransaction offer.

Now the the Counter Strike: Global Offensive's survey is needed to be analyzed. With the aim to have a representative survey, it was needed to have a sample size of 96 respondents. Fortunately, within this survey 107 responses were collected and 100 of them used to make microtransaction at least once in the Counter Strike: Global Offensive. How it was in the case of DOTA 2 survey the average and the medium numbers will be found out and then the table with intervals of annual “check” will be constructed. The average annual “check” is 2737.9 rubles what is considerably lower comparing to results of DOTA 2 survey. The median value is also lower comparing to the results from DOTA 2 survey - in the case of Counter Strike: Global Offensive the median annual “check” is 2550. Now the table with intervals should be presented:

Table 20

Intervals of “annual” check

Intervals of annual “check”

Number of respondents within the interval

Percentage

1 - 1000

10

10 %

1001 - 1999

21

21 %

2000 - 3500

47

47 %

3501 - 5000

16

16 %

5001 - 10000

6

6 %

100

100 %

Therefore, the table shows that the overall number of intervals are lower, because none of respondents used to waste more than 10 000 rubles per year on in-game items in Counter Strike: Global Offensove. Nevertheless, once again the most popular interval with the highest number of respondents within it is from 2000 to 3500 rubles as it was in the case of DOTA 2 survey. At the same time, the interval with the lowest number of respondents is quite different in the case of DOTA 2 - it is the highest interval from 5001 to 10 000 rubles. Analysis of survey implies the researching of different types of microtransactions and as it was in the case with DOTA 2 survey, the average annual “checks” will be calculated, because the third and the fourth questions are similar to the DOTA 2 survey - on what type of microtransaction within Counter Strike: Globall Offensive players waste the most amount of real money and what amount do they waste annually. The table shows these results from SPSS:

Table 21

The monetization from different type of microtransaction in Counter Strike

Capsules

Battle pass “Shattered Web”

Prime account

Cases and keys

Other items from the Steam

N

13

14

9

27

37

Mean

1303. 85

1628. 57

1017. 78

2523. 08

2787. 88

Median

1000

1750

1020

2450

2600

Mode

500

2000

1020

2000

2000

Std. Deviation

920. 25

620. 71

6. 67

1336. 65

1074. 64

Minimum

300

800

1000

600

1600

Maximum

3000

3000

1020

7000

5000

First of all it is seen that comparing to DOTA 2 results of survey, in the case of Counter Strike: Global Offensive, respondents prefer much more items from the Steam market - it means that players prefer to buy diverse cosmetics like weapon skins, gloves, knives from the Steam market and not gamble these items from the cases directly within the game. Prime account has the lowest average annual monetization and at the same time it has the lowest amount of players who waste the most money on this type of microtransaction. 27 percent of respondents are wasting the most amount of real money on such type of famous microtransaction as cases and keys from these cases with the aim to gamble and try to get the skin, gloves or knife which will cost much higher comparing to the cost of the case and keys. Battle pass also did not show such impressive results as “The International” battle pass did from the DOTA 2 survey. Other questions in the Counter Strike: Global Offensive's survey had the same concept as they were in DOTA 2 survey, but were changes in some details. Thus, the fifth question was completely the same as it was formulated within DOTA 2 survey - if respondents ever felt that the game forces them to purchase some in-game items via real money. As it was in the case of previous survey for other free-to-play online game, majority of surveys never had this feeling - only 38 players within the survey stated that they used to have the feeling of being forced to buy some in-game items. Sixth question was reformulated slightly - respondents were asked if they purchase different cosmetics such as skins on weapons, gloves and knives from the Steam market or they are attemping to gamble these items from cases directly from the game. This question is needed with the aim to estimate the monetization from the cases and if respondents still believe that it is easier to get needed item by gambling than purhcasing it from the market what would mean that Counter Strike receives only 10 percent in this case. The results of this survey showed that 33 respondents (33 percent) are using Steam market to get needed weapon skins, gloves and knives. However, 23 players are trying their luck by opening cases within the game what gives Counter Strike much higher profit generation. Nevertheless, as it was in the case of DOTA 2, the majority of respondents are using both ways of getting needed skins - sometimes they are using only Steam market with the aim to get neccesary items and sometimes they are trying out their luck by opening cases in the Counter Strike. Only 5 respondents have never purchases any cosmetics such as weapon skin, gloves or knives. The final question was completely similar to the last question from DOTA 2 survey - if players would return to the game after taking a break in the case if new offer of microtransaction would be availabed in the Counter Strike: Global Offensive. Survey showed some dispersion within results, because 19 respondents stated that they would definitely check the new microtransaction offer and visit the game for this purpose. 58 players stated that they are not sure, but more likely that they would visit the game. 20 respondents stated that they probably would not visit a game only because of new offer of microtransaction and only 3 respondents within survey claimed that they would definitely not visit the game in the period of the break from the game only because of some new offer of microtransaction.

According to the results of both surveys it is possible to say that the second hypothesis appeared to be true, because within both of DOTA 2 and Counter Strike:Global Offensive survey, more than 50 percent of respondents used to perform the action of microtransaction at least once per year in both researched online free-to-play games.

6. Conclusion

In this section results will be discussed and the conclusion will be formulated what is going to summarize all the work. First of all, this work showed that different types of microtransaction have diverse profit generation and different “popularity” within players what lead to the amount of wasted money on some specific type of microtransaction. The first analysis will be done for DOTA 2 survey. For more simple presentation of different types it is better to construct a table:

Table 22

The level of successfulness of different type of microtransaction in DOTA 2

Type of microtransaction

Amount of respondents who waste the most amount of money on this type

The average annual “check” for this type (in rub)

Result of calculation

The level of successfulness

Treasures

16

2196.67

35 146. 72

C

“The International” battle pass

42

5309.29

222 990. 18

A

DOTA PLUS

16

1675

26 800

E

Other items from the Steam market

19

2163.16

41 100. 04

B

“Arcana” items

9

3522.22

31 699. 98

D

Tableshows that the most succesfull item which has the highest monetization is “The International” battle pass, because 42 respondents out of 102 used to waste about 5309 rubles annually only on this type of microtransaction what shows the dominance and the effectivity of this type of microtransaction. Then the other in-game items from the Steam market has the “B” level of succesfulness, because about 19 respondents out of 102 chose this type as their favorite and they waste about 2163 rubles only on this type of microtransaction annually. Then treasures go with the level of succesfulness of “C”, because 16 respondents claimed that they are wasting the most amount of money on this type of microtransaction - about 2196 rubles annually. However, “Arcana” items have only “D” type of success and the major reason for this can be a fact that there is only 13 type of microtransaction that can be purchases within the game. Moreover, some of unique “Arcana” items can be received within “The International” battle pass on some levels. Therefore, battle pass takes some monetization from “Arcana” items at this point. Finally, the least succesfull type of microtransaction with the least monetization is the DOTA PLUS. Probably it is due to the fact that it works as a subscription and players do not gain all the benefits at the very start of this microtransaction - the more players are subscribed the more advantages from DOTA PLUS they get.

For other survey same table can be constructed with the aim to make a conclusion about the most and the least succesful type of microtransaction within DOTA 2 and Counter Strike: Global Offensive:

Table 23

The level of successfulness of different type of microtransaction in Counter Strike: Global Offensive

Type of microtransaction

Amount of respondents who waste the most amount of money on this type

The average annual “check” for this type (in rub)

Result of calculation

The level of successfulness

Capsules

13

1303. 85

16 950. 05

D

“Shattered Web” battle pass

14

1628. 57

22 799. 98

C

Prime account

9

1017. 78

9 160. 02

E

Cases and keys for these cases

27

2559. 26

69 100. 02

B

Other items from the Steam market

37

2724. 32

100 799. 84

A

As table shows, the most succesfull type of microtransaction in Counter Strike: Global Offensive according to the results of survey is the other items that players are buying from the Steam market. The second from the top is cases and keys for these cases. The least profitable type of microtransaction is a Prime account in Counter Strike.

Therefore, these 2 tables help to conclude that according to the collected data from two surveys with more than 100 respondents, the most succesful type of microtransaction in DOTA 2 is “The International” battle pass. Probably it is because of the fact, that within this type of microtransaction, players can get the rarest items and some of them won't be available for trading later. Also, as it was stated, nearly every battle pass each year have its unique “Arcana” items, treasures, skins for characters. Therefore, it is one type of microtransaction that consists of other type of microtransaction and when players purchase only battle pass, they are getting the opportunity to get treasures, rare skins and untradable “Arcana” items for “free” by playing the game. In the case of Counter Strike: Global Offensive the most succesfull item is the other items from the Steam market. There is also a logical interpretation of such results. The reason for this is a fact that chances of droping a rare items within cases in Counter Strike are significintly lower comparing to DOTA 2 and players want some specific skins which much easier to buy directly from the market. At the same time, cases in Counter Strike has higher amount of items within one loot box what significantly decreases chanses of getting some specific skin that a player wants. At the same time, cases and keys for these cases also have enourmous monetization, but it is lower comparing to skins from the Steam market and this is why it is only “B” type of microtransaction.Battle pass “Shattered Web” was not such succesfull within Counter Strike: Global Offensive as it is in the case of DOTA 2. It is probably because of the fact, that players were not able to receive such any actually unique and rare items that can not be purchased on the Steam market and if any item from battle pass can be purchased on the Steam market or gambled within some cases, then there is no actual point to waste immense amount of money with the aim to get some specific item from the battle pass. The Counter Strike did not use numerous amount of features that were able in the “The International” battle pass such as cards with players, there was no bundles and in general battle pass “Shattered Web” was suffering from much poorer design comparing to “The International” battle pass. It means that this type of microtransactions on a completely different levels of success. Capsules are the “D” type of success, because in the vast majority of capsules only different stickers on weapons are included and there is no actual skins. Probably players are less interested in stickers only and rather would waste their money on the weapon skinsm gloves or a knife. The least succesful type is Prime account in Counter Strike and the major reason of this is a fact that players can simply get it for free by playing a game and upgrading their level. However, some impatient gamers can not wait and they are deciding to buy this Prime account.

Immense amount of work was done with the aim to check if there is a correlation between players online and amount of sold items on the Steam market - amount of trades in other words. The results showed that only one item had strong and positive correlation, while the vast majority of researched in-game items had just positive and slight correlation. The average correlation for 3 cases from Counter Strike: Global Offensive is 0. 77 and it is possible to say that hypothesis in the case of Counter Strike was tested to be positive and can not be refused - there is a correlation between players online and amount of sold items on the Steam market in the Counter Strike. This correlation is positive and equals to the 0. 77. The analysis of DOTA 2 in-game items showed that the average correlation for 3 researched “Arcana” items is 0. 451 and in this case it is possible to say that there is super slight and positive correlation between researched variables.

The analysis of such unique microtransaction as “The International” battle pass in DOTA 2 showed the complextity of this specific microtransaction and that there is a solid reasons why game does not allow players to get the whole spectre of opportunities after the release of battle pass - they want to increase online in other months by adding new treasures, bundles, skins for characters and this is what will motivate players to return into the game. Numerous charts proved that battle pass nearly every year had some short period of a sharp growth in revenue which was caused by some new treasure, bundle or other in-game offer that is available within battle pass. Moreover, both surveys for DOTA 2 and Counter Strike: Global Offensive showed that vast majority of players will come back to the game after a break if some new microtransaction (as battle pass, new “Arcana” item or new case in Counter Strike or something else) will be released within the game. In the case of Counter Strike survey 77 percent of respondents who ever used to make a microtransaction in the game claimed that they are going to come back to the game. In the case of DOTA 2 survey just 77 respondents stated that they are going to return to the game and 29 of them were sure about this while in Counter Strike survey only 19 respondents were sure about their come back to the game after a break. Within both of surveys the question if respondents ever had a feeling of being forced to pucrhase some in-game items also was present with the aim to understand if microtransactions can be noticeable for players and if players feel the pressure that the game forces them to perform the action of microtransaction. It turned that in the case of DOTA 2, majority of respondents have never ever had a feeling of being forced to perform a microtransaction and the same situation is for Counter Strike: Global Offensive: the vast majority of players have never ever had a feeling of being forced to perform a microtransaction which was promoted by the game. The last question showed that within DOTA 2 21 reposendents used to buy “Arcana” items through the game market what is a high number and it means that the game receives the whole price while players are using in-game market. In the case of Counter Strike: Global Offensive 23 percent of respondents are using cases with the aim to get neccesary cosmetic skins and it also leads to higher revenue for game developers, because players are trying to gamble some specific skins and in average it is much more profitable than just purchasing a skin from the Steam market.

Moreover, the null hypothesis was tested and it appeared that in both DOTA 2 and Counter Strike: Global Offensive it was rejected, because an independent t - test which was conducted in SPSS showed that there is a significant difference between means of months when there was a new offer of microtransaction and when there was no microtransaction. In more details, it is possible to claim that in the case of DOTA 2, the new microtransaction brings about 45 015. 750 more players to the game and in the case of Counter Strike: Global Offensive, the new offer of microtransaction (new case or new battle pass) brings to the game in this month about 48 722. 217 and it is a significant number. Therefore, it is possible to claim that players online depend on new microtransaction and at the same time it proves the validity of results from both of surveys, because it showed that majority of respondents would come back to the game after a break only because of new microtransaction.

In general, microtransactions are playing a crucial role in the overall revenue of the game. According to Statista, DOTA 2 had a revenue in 406 million of dollars in 2017 (Gough, 2019). However, it was found out within this research, that only “The International” battle pass in 2017 brought about 70 million dollars of pure revenue to the game. Other types of microtransactions are less profitable, but it is surely that in general profit from microtransactions was about 160 million of dollars what means that DOTA 2 for sure gets 40 percent of its income from microtransactions.

Therefore, in the end, it is possible to say that within this immense amount of work the initial goals were successfully accomplished by a huge analysis of diverse type of microtransaction in such free-to-play online games as DOTA 2 and Counter Strike: Global Offensive. It was shown that different micrtotransaction has different monetization and that some of them are not that attractive for players, while some of them are motivating players to visit a game over and over again. However, the diversity of microtransaction leads to higher monetization in the end. The research question was formulated as: how microtransaction affects the monetization in free-to-play online games and the research showed that microtransaction actually increases amount of players online on a monthly basis what was tested within the null hypothesis and it leads to the higher profit generation, because within the second hypothesis it was tested that higher amount of players online leads to the higher profit generation, because there is a slight and positive correlation between amount of players and amount of sold items. Finally, it was proved via both surveys that majority of respondents used to perform the action of microtransaction at least once in their gaming career.

References

An o...


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