It’s great that you guys investigated this and made a suggestion to TIOBE, but because of its methodology, it remains one of the noisiest measures of programming language usage/popularity.
Composite measures like Redmond and IEEE Spectrum are still a bit shaky, but at least they are better equipped to catch measurement anomalies (eg one component experiencing wild fluctuations that does not show up in other components).
In the long run, a better solution could be a composite index with
- a transparent data collection process (all scripts open source),
- raw data from this archived with open access,
- with a latent process estimated using a robust statistical filter to produce reports at some frequency (this step is crucial, otherwise the noise swamps all trends up to medium run).
I know this is not for the Julia community to solve, but perhaps NumFocus could get behind something like this.