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The process of scoping out creators to create a successful sponsorship is extremely difficult. Brands work overtime filtering through the 37M channels on YouTube in order to find the handful of influencers that create content in a specific niche, reach and engage with the optimal audience, and have the highest chance of influencing potential consumers.
Over the years, we have developed (and continue to update) a platform that does the filtering for brands and agencies - everything from grouping YouTubers by specific topics/categories to specifying ideal video views and projected views. Recently, we added a crucial metric - sponsorship score.
A sponsorship score is a metric displayed as a number that tells us the strength of a channel in regard to sponsorships. Does the channel do a large number of sponsorships? Are the sponsored brands seeing good results? It’s meant to deliver basic information at a glance. So if a specific YouTube channel has a sponsorship score of 9 out of 10, they are obviously veterans at promoting content and are giving brands the results they like to see. However, if a channel has a sponsorship score of 1, it doesn’t mean that channel shouldn’t be considered for a sponsorship opportunity because they might just be new to the game. But, it’s definitely worth taking a closer look at their YouTube activity.
First, we let our cluster collect aggregated data on past sponsorships until a certain threshold, for example, the last 12 months. Then our system runs a complex calculation and delivers a final single number. All of this is done automatically within a fraction of a second. The calculation is using “live” data - so, whenever a channel publishes new content, its sponsorship score can potentially change.
The final score is composed of two main components: the amount of unique sponsoring brands and quality of these relationships. For example, a huge amount of hit-and-run sponsorships (brands that sponsored a single piece of content and didn’t return to the channel) is going to produce a poor score. The second aspect - quality of the sponsorships - focuses on whether or not a brand received its ROI. One big way to highlight the sponsorship quality is by seeing how many times the brand came back to sponsor the same channel. So, in general, channels that have 5-10 ‘regulars’ (brands that sponsored their channel a number of times) will score higher.
This sponsorship score is displayed on our platform, saving you from having to do the calculations. This, in turn, allows both brands and creators to get a fast and clear understanding of whether or not a YouTube channel is ‘worth’ sponsoring. It will also come into play with negotiations between potential brand and creator integrations - for example, if a YouTuber has a lower sponsorship score, the brand may negotiate a lower rate.
It's super important to brands because it shows them the score that is most relevant for the content they are looking for and the ones that would be the best brand fit. So if a brand is looking to sponsor Food related channels, they would want to find the channels that score the highest for them in the food category. By having a simple number, brands can easily come to a conclusion without needing to do the research themselves.
It’s important to stress that the sponsorship score is just one metric that can be hugely helpful in understanding sponsorships but should be considered alongside other data points like engagement, projected views, and the actual content of the channel.
Although a higher score does indicate a higher chance of success, all forms of marketing have risk factors no matter what. A specific channel might have a high score but it doesn't guarantee positive ROAS - the chances that it will perform well are very high though. With that being said, brand sponsorship history is a large factor in our sponsorship score. So if a channel is relatively new or doesn't have a lot of sponsorship experience, its score will be significantly lower than one of a "network channel." However, It's still a good idea to sponsor channels with lower scores as you might be able to discover a channel on the rise or find a small channel that really connects with your brand. With all that being said, the sponsorship score will become a major player when it comes to rate negotiations. Using the sponsorship score, brands can negotiate lower rates for channels that have lower scores because the risk of promoting these channels is higher - but, the same can be said about channels with higher scores (it may boost the creators confidence to ask for a higher rate).
Brands can feel confident that the creator knows how to handle sponsorships - everything from sending assets on time to understanding how to build the ad-read in the most successful way. These creators may save brands a lot of time and energy because their experience will reduce the chances of make-dos, mistakes in displaying the promotional assets, and ensuring the brand and its products are displayed in the best way.
Yes, the content itself. Many brands have red-lines, which are hard to disqualify with the sponsorship score filter. For example, if you are looking to sponsor news content but don’t want to integrate with a super political channel, you’ll need to investigate on your own whether the channel is actually a good fit or not (sponsorship score aside).
Another point to keep in mind is that our data doesn't look at the actual ROAS (return on ad spend) delivered by each creator - especially because each brand calculates this differently. Instead, we look at publicly available data (like, how many times a sponsoring brand returned to work with the same channel) to make educated guesses about which partnerships have a positive ROAS.
Also, it’s important to keep in mind that while channels with a higher score are quite professional when it comes to sponsorships, the number doesn’t take into account the reliability or responsiveness of a creator.
The sponsorship score should help both brands and creators get a better understanding about sponsorship behavior. Instead of brands needing to take a deep dive into any and every creator they are interested in - which includes looking at how many sponsorships they have done in the past, how many of those brands returned, did the brands actually see good results, etc - they can just look at the score and get a pretty good understanding of what to expect.
If you have any questions about sponsorship scores, do not hesitate to reach out.
