If some forecasting was built into the dashboard, I think you'd see lower churn of newsletter creators in the first and second year. They need to be able to visualize what their creativity could become. I may be wrong but my impression is there is a blind spot.
The majority of newsletter writers don't seem to take a long-term view of what paid subscriptions. Plus sponsored ads with flat fees can become in terms of a side gig.
If Substack did what Paved does, and took 15% instead of 30%. What a different business model this would all be for you and us.
Yea that approach makes a ton of sense essentially applying a % of the total. Yea makes sense, especially as you said, with the retention behaviours being similar. Thanks a ton! Excited to read the rest of the articles on your page
This is a really great article. I'm wondering how it differs (or not) for instances when forecasts need to be at a product level. For example a company offers several categories of products and wants to forecast the subscription revenue that will be generated from each category. Would it be just doing this but for each product and them summing it all together? or is there a way to think about it that'll make it less cumbersome
Great concept and model, Reid. I’d love to take a look at the actual file if you wouldn’t mind sharing a copy. Also, curious why you assumed in the “% of subs remaining after“ chart that 100% of annual subscribers would be retained after year 1. Why wouldn’t some churn after year 1?
Great article Reid...I'm largely just here to ogle that eye chart...what a beaut! And thanks Tony for giving such an intimate peek into your business...
...curious if you have any thoughts on how to model the growth opportunities for the business expansion components (hiring a growth lead vs. starting a pod vs. buying some programatic ads, etc.)?
I wish these were somehow part of what we share with / show writers; these are all so good and seem really useful and you could see versions of them as being “official Substack documentation” or whatever!
If some forecasting was built into the dashboard, I think you'd see lower churn of newsletter creators in the first and second year. They need to be able to visualize what their creativity could become. I may be wrong but my impression is there is a blind spot.
The majority of newsletter writers don't seem to take a long-term view of what paid subscriptions. Plus sponsored ads with flat fees can become in terms of a side gig.
If Substack did what Paved does, and took 15% instead of 30%. What a different business model this would all be for you and us.
Yea that approach makes a ton of sense essentially applying a % of the total. Yea makes sense, especially as you said, with the retention behaviours being similar. Thanks a ton! Excited to read the rest of the articles on your page
This is a really great article. I'm wondering how it differs (or not) for instances when forecasts need to be at a product level. For example a company offers several categories of products and wants to forecast the subscription revenue that will be generated from each category. Would it be just doing this but for each product and them summing it all together? or is there a way to think about it that'll make it less cumbersome
Great concept and model, Reid. I’d love to take a look at the actual file if you wouldn’t mind sharing a copy. Also, curious why you assumed in the “% of subs remaining after“ chart that 100% of annual subscribers would be retained after year 1. Why wouldn’t some churn after year 1?
Great article Reid...I'm largely just here to ogle that eye chart...what a beaut! And thanks Tony for giving such an intimate peek into your business...
...curious if you have any thoughts on how to model the growth opportunities for the business expansion components (hiring a growth lead vs. starting a pod vs. buying some programatic ads, etc.)?
I wish these were somehow part of what we share with / show writers; these are all so good and seem really useful and you could see versions of them as being “official Substack documentation” or whatever!
Another stellar analysis. Very helpful and keeps me thinking about ways to stay ahead of "both" curves...