In the last phase of our research, we tested if participants will contribute real money to a content maker they just encountered based on the visibility of different counters. In the first experiment the counters were prompts describing different type of relations between the content makers and viewer. This experiment elaborates the insights from the previous research.
In the second experiment, we used dynamic counters, indicating a change in the number of viewers or amount of money, to follow how their visibility influences willingness to pay. We asked the participants to share real money with the content maker from a bonus they received in the research study. Surprisingly, almost 1/2 of the participants paid something and supported the content maker.
Insights:
1) Counters showing money and time work better for "one to one" (EM) relations rather than community-oriented "one to many" interactions (CS).
In simple English: it is better to utilize counters that indicate the resources the content maker used for production rather than indicate the support of the community.
You will find more about this line of research in our previous post Time is not money and supporters are not always communal: insights into counters and widgets.
Design of the study:
We used prompts/counters that indicate EM (equality matching) or CS (community sharing) relations based on the visibility of hours or money the content maker either received from the community (CS) or invested (EM).
Prompts and counters:
a) Indicating CS relations based on money (community paid for the content XYZ, will you support the content?):
"The creator has received 200$ from his followers who backed this video that became the most popular content of the week. Please consider sharing part of your bonus with them.
How much from your bonus will you be willing to share with the creator?
b) Indicating EM relations based on money (content maker invested XYZ, will you compensate/support?):
"The creator invested 200$ into making this video, please consider sharing part of your bonus with them. How much from your bonus will you be willing to share with the creator?
c) Indicating CS relations based on time spent (community spent this much time watching, will you support the content?)
"Followers jointly watch 200 hours of videos from this content maker every week, making him the most popular content creator. Please consider sharing part of your bonus with them."
d) Indicating EM relations based on time spent/invested (content maker spent this much time making the video, will you compensate/support?):
"You watched 200 hours of free content from this channel, please consider sharing part of your bonus with them. How much from your bonus will you be willing to share with the creator?"
Results:
Counters and prompts indicating EM (equality matching relations) received higher bonuses (averages) no matter if they communicated money or time. Participants were more willing to contribute to something involving one-to-one, tit for tat relations: they were more willing to pay a maker who invested 200 USD or whose videos they watched for 200 hours for free.
Counters and prompts indicating hours in EM relations polarized the reactions into giving full amount of the bonus or 0 cents.
The prompt "You watched for free, pay something" seems to unite the responses into "either be very generous or ignore" based on the level of interest in the content.
In the case of CS (community sharing) counters the reactions to prompts indicating money triggered similar polarization as in EM (pay a lot or nothing). This differed from CS counters indicating how much time the community spent watching the video (to make it popular) that attracted some of the worse results in terms of bonuses. Almost 1/3 of the participants decided not to share their bonus (0 cents). In contrast, the reactions to the EM counter communicating that the creator spend 200 USD gave some of the best results – it made 1/3 participants contribute average of 10 cents.
Counters communicating time seem to polarize the reactions (more people gave 0 cents under CS and EM), at the same time the EM-time based counter also triggered some of the most generous reaction (20 cents bonuses) indicating that there is a particular group of viewers that appreciate content makers' time.
Participants that make more money online tend to be more generous to content makers. The most generous participants were the ones that already pay more than 50 USD on content per month.
2) Showing less is sometimes more, especially if it is about money
Design of the study:
In the next stage we decided to follow the effect of the counters as live and dynamic visual props indicating real-time number of viewers or amount of money the content attracted (compared to “no counters” situation). The counters displayed a positive trend in viewership/funds, meaning that participants saw that the content maker is gathering more attention/funds as they watched the video. We were curious to see the level of “generosity” (sharing of the bonus) based on the type of counter participants experiences.
There were three types of scenarios:
- participant watches a video with visible members/viewers counter (showing a positive trend of viewership overtime)
- participant watches a video with visible money counter (showing a positive trend of funds overtime)
- participant watches the video with no counter.
Whether there was a counter (moving up to the level of 200 viewers or USD) or no counter, the participants were asked how much money or viewers the content attracted, to see if they noticed the counters.
In the case, no counter was shown, we asked:
How many viewers do you think supported this video?
How much money do you think the creator makes per video?
Money Counter question:
How much money do you think this creator makes per video?
Viewers/members Counters question:
How many viewers do you think supported this video?
After watching the video with or without counters, we offered them an extra monetary bonus asked them to share part of it with the content maker:
Please consider sharing part of your bonus with the creator.
How much from your bonus will you be willing to share with the creator?
Results:
Most participants paid attention to the counters and made correct guesses when the counters were visible. Of the participants exposed to counters, around a half answered correctly with others making relative small mistakes in the estimation. Of people who received a video without a counter, most assumed the content maker had less viewers/money relative to the counters we created.
However, the invisibility of the counter in fact increased generosity.
What they guessed and perceived the content maker makes or attracts differed depending on whether the focus was money x viewers. ** When participants observed an ongoing positive trend in terms of funds contributed, they were less likely to contribute themselves**
When no counter was present, the generosity depended on how much they assumed the content maker makes from the viewers: if they thought the content maker makes a relatively low amount (15-150 USD monthly from the video), the average bonus was 6 times more compared to participants who actually saw a money counter and indicating a similar amount). If they guessed the content maker makes a relatively high amount (more than 200 USD monthly), then they paid around 10 time less (0.4 cents on average) compared to 3.7 cents when they had visible counter.
This repeated with the counter showing viewership: seeing the counter versus guessing the number of viewers made the participants less generous in terms of average bonuses. Still, seeing or guessing more viewers did not lead to the same dramatic drop as in the case of money counters or guesses (the participants did not “punish” the counter maker for being popular).
Conclusions:
Not showing any counters fared better in terms of supporting participants' generosity, and the counter showing viewers had limited positive effect (their visibility was less detrimental compared to the money counter). In the case of a visible viewers counter, the participants were supportive of beginners with 11 – 50 viewers. We could assume that using no counters or counters communicating low number of viewers (11-50) is good for beginners as they attract more donations from users. On the other hand, counters communicating money seem detrimental to beginners. If the participants guessed that the content maker makes too much or too little (0 or above 200 USD), they become less generous (0 and 0.4).
Not showing a counter seems to work better for new content makers, since people assume they need their support. However, counters that show the level of content makers popularity via viewership are steadier in eliciting funds compared to those showing monetary donations. In the latter case, the counter may provoke polarizing effects once people believe the content maker "has enough" funds.
Top comments (2)
As always, it's fascinating to read your research @denisakera . Great job!
These are some really interesting findings, and we'll try to implement them in our work.