NYT Write-Up
For the first time in years, investors have become pessimistic on the main drivers of NYT’s business model – its digital news subscriber potential & its digital news pricing power. This write-up examines base rates for both of these drivers.
For the first time in years, investors have become pessimistic on the main drivers of NYT’s business model – its digital news subscriber potential & its digital news pricing power.
NYT’s share price is down ~25% from its February highs after 2021 Q1 net digital news subscriber additions were lower than expected (167k net adds for the quarter vs ~215k expected).
The Company’s news subscriber potential is a function of its readership base and its conversion rate of that readership base into paying news subscribers. The Times has >100m registered users today, which we’ll use as a snapshot estimate of The Times’s readership (one could also consider MAUs and other gauges of TAM, all of which we explore in the write-up attached below). The Times has 6m news subscribers across print & digital, implying a 6% conversion ratio today.
Investors are questioning if The New York Times is hitting the ceiling of the total news subscribers that they can realistically acquire. This implicitly means investors are bearish on either NYT's registered user count increasing and/or NYT being able to convert substantially higher percentages of those registered users into paying subscribers.
There is no talk among investors about future price raises.
I read Superforecasting a few weeks ago and it inspired me to look into base rates for NYT, particularly around pricing growth and conversion ratios of other best-in-class freemium digital media businesses like Spotify and Tinder. The results are extremely interesting.
This post is the first stock write-up I've done on the blog, and the first time I'm going out on a limb by making explicit forecasts (which will undoubtedly be precisely wrong and will need to be updated over time). I'll do more of these posts in the future but the timing will be sporadic.
You can read the memo at this link.
JC note to reader: none of the analyses are perfect. I use multiple analyses in the hopes that individual imperfections/errors will cancel out. I will track the data over time and adjust my forecasts along the way. With that said, if you see something you disagree with, please let me know as I want to be accurate in my forecasts much more than I want to be proven right.