Why We Built SongScore the Way We Did
Every music-testing company will tell you their method is scientific. Most won’t tell you why — which choices they made, what they rejected, and what the research actually says. Here’s ours, in plain language.
Oh, and we did we mention that Songscore is is a fraction of what most of those dinosaur music test companies charge? you get the same, scientifically proven research methods for less than $150 per month.
At Songscore, we follow accredited research techniques and employ the Likert Scale. We decided when we built Songscore that we wanted to use the most scientific, widely accepted (by scientific standards) approach we could, so that results could be consistent over time and prove the most valuable.
Here is a brief guide as to why we do things the way we do:
A 5-point scale, with a real neutral option
We use the Likert scale — the same 5-point structure used across decades of published survey research. Some researchers argue for more points; almost none argue for fewer, and none argue for removing the neutral option.
Here’s why the neutral option matters: if a listener genuinely feels neutral about a song and you don’t give them that option, you’ve forced a dishonest answer — and your data is compromised before the survey even ends. In practice, with a proper sample size, neutral responses barely move the needle on your final scores anyway. What matters most is the relationship between the 2 negative and 2 positive responses, and where a song lands relative to everything else it’s tested against.
Labeling of 5 points
Longwood University cites the finding of Weijters who found that people are attracted to labels. So, for example, if we only labeled 1 as “dislike” and 5 as “like” and left 2, 3 and 4 as unlabeled, people would tend to choose 1 or 5 more often but for no reason. Thus, all 5 options are always labeled.
Why comparison matters more than the raw number
A song scoring 4.01 sounds solid — until you learn the survey’s average is 4.55 and ten other songs beat it. A raw score alone tells you almost nothing. What tells you something is how a song compares to the mean for that specific audience.
That’s the whole idea behind Momentum Score™ and Z-Score: not “is this song good,” but “how is this song actually performing relative to everything else your listeners heard this survey.” It’s the same logic in this section, just given a name and a chart.
Every point on the scale gets a label
Unlabeled scale points bias your results. If only the two ends are labeled (“dislike” / “like”) and the middle three are left blank, people gravitate toward the labeled extremes for no real reason. So every one of our 5 points is labeled, always.
You can change your labels any time — just contact support with your new list. One thing worth knowing: changing labels resets your baseline. Don’t compare scores from before a label change to scores after one, and once you pick new labels, keep them consistent going forward.
Why there’s no “national average”
Imagine averaging together the hundred best regional chicken soup recipes in the country into one “ultimate” recipe. It wouldn’t taste like any of them — you’d get something that represents no one’s actual preference. Testing music works the same way: blending results across different markets, formats, and recruitment methods doesn’t produce a more accurate answer. It produces a fiction. What you actually need is your market’s answer, from your listeners — which is exactly what SongScore gives you.
Why we recommend 400+ spins before testing a song
Advertisers rely on Optimum Effective Scheduling (OES) — the idea that a listener needs to hear something roughly 3 times before it registers. Music works the same way. Listeners can’t form a real opinion on a song they’ve barely heard. We recommend waiting for at least 400 spins before testing — you’re welcome to test earlier, but know that early results may not reflect where the song actually lands once it’s had a fair chance.
It’s your research — you’re in control
Hide titles or artists, use your own custom hooks, set your own labels — SongScore adapts to how you work, not the other way around. And now, with the AI Assistant built into your dashboard, you can ask questions about all of this data directly — no spreadsheet required.