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An advertiser would then be able to filter the creators by category or subject and then weight their scores by how important they are to the advertiser.
This example uses a 0–100, 0 being not important at all and 100 is extremely important.
For example, they could say a large number of YouTube subscribers is very important, or the audience size doesn’t matter as long as the overall watch time is over a certain threshold.
Or, they could specify that a minimal YouTube following is okay as long as there is meaningful engagement on Twitter.
A more balanced distribution
We’d end up with a proportionate distribution across the number of creators, and their respective scores (after weighting) would determine who earned what from the budget (in this example, $25,000).
Creator 6 in the example earns the most as they have the largest TikTok following and a good Like ratio on the platform — which was most important to the advertiser.
One positive is a creator who has a relatively small audience but has doubled down on a specific niche on a particular platform has greater monetization potential instead of the entire budget going to a single creator.
Another positive is that the advertiser can tweak the importance of specific tactics knowing that several creators will be appropriately compensated.
A creator who has spent a long time building a huge audience would probably wonder why they’d be willing to split proceeds with more creators — which is, of course, a valid point — but it would be interesting to know if they would ultimately earn more through a greater number of smaller deals or fewer higher-paying deals.
A counter-argument
John Bardos offers a complete counter to this in his article There Will Never be a Creator Middle Class and Why That’s Good. There is a reason that the world works like this after all; creators have to play by market rules.
But ‘market rules’ do change, and often — and most creators on these platforms are ultimately beholden to the whim of the advertiser.
Considerations
There are a few considerations to this model that could wildly affect its accuracy:
- You would still need a system to ensure the creator promoted the product or service to the advertiser’s satisfaction.
- You would need an ongoing method to measure the metrics for each creator.
- Ideally, you would have some analysis of potential earnings comparing a high number of lower-paying deals over a low number of high-paying deals.
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