@hutch_golf You cooked 🔥. Gotta do a firmware update or six on my link bc I’m the problem case that got annoyed with the sensors, excited to try. Would also be very curious on the tech stack / primitives for the AI detection+classification 😅
@bernhardsson @d_mccar @faderp@fader (6/7) Check out the lovely BTYD, BTYD2 and CLVTools packages in R or lifetimes in Py. They combine survival models with probability distributions for the underlying behaviors… ‘die’ (churn), ‘buy’ (transact at time(t) or not, quantity, $ spend)
@bernhardsson (2/7) Those distinctions matter in that continuous vs. discrete tells you when transactions can occur. Contractual vs. non-contractual tells you whether customers ceasing to be customers (customer churn) is observable.
@d_mccar ‘Tale of two customer bases’ story incoming for per seat models depending on mix btwn “landed” and “expanded”. “Landed” more likely on monthly contracts + LIFO for IT teams looking to cut. Ouch. “Expanded” = more likely annual / multi-year and better positioned to weather storm.
Our latest, The Economics of Customer Businesses, is out. It is based on the principles of customer-based corporate valuation (CBCV). I benefitted from lots of conversations with @d_mccar and @trengriffin, as well as the work of @faderp and @rgmarkey.
https://t.co/CjktJJxSOC
With all of the scary stuff going on, here is a list of 3 of my favorite things: (1) the little whisper bark dogs do before a real bark, (2) Luda’s verse on Holidae In, (3) when enough of the taco fillings fall out to make a new taco with