The Ledger
Every statement that passed quotation and attribution checks. Mix any filter with any other: certainty 1/5, debate potential 5/5, or both at once.
why aren't all 11 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 0 checkable ones are still open, waiting for their date. predictions held up or didn't; assertions are supported or contradicted. on every card: ▮▮▮▮▮ certainty · ▮▮▮▮▮ debate potential. speakers are clickable
Price: Largest SaaS customers are outliers needing dedicated service layers
“Largest customers tend to be outliers and have very unique requirements in which case you need to overlay certain levels or levels of
Service on top of that.”
Price: Zendesk acquired first 10,000 customers with zero salespeople
“Zendesk got its first 10,000 customers without any salespeople, and what they figured out was a way to actually take something that was Kind of simple that everybody needed, which was customer service, but cost hundreds of thousands of dollars and loads of con…”
Price: Zendesk avoids costly consulting to drive enterprise software growth
“And that's what we try and do today with, even as we move more up market, we try and make our software such you don't need to spend hundreds of thousands of dollars on consulting, but you know, you can deploy it very quickly. And that's where a lot of the ente…”
Price: Bundling unwanted free features makes customers feel they are overpaying
“Sometimes putting things in as free can actually add complexity to the customer if they're not going to want to use it and also makes them feel that there may be over overpaying because they're getting things that they actually don't want to use.”
Price: Long-tail features with narrow utility enable premium SaaS pricing
“Typically where a long tail exists, then there's an opportunity to actually add the premium price to those into those features because they have very specific utility to a small number of customers.”
Price: Deep cohort analysis of 100 customers beats top-down metrics
“So actually you can get probably more intelligence a lot of time out of taking a hundred, a sample of a hundred customers and looking deep into what those customers are doing, whether it's when did they adopt, what features are they doing? You've got a big eno…”
Price: Zendesk charges $1 per AnswerBot resolution to capture $10-$20 value
“The value to a customer of them not having to have that question go to a support agent, which tends to cost, you know, can cost tens, 15, tens, 20 dollars is very, very high. So we decided to price that separately, and we charge one dollar per resolution on th…”
Price: Dollar Shave Club used AnswerBot to improve service, not cut headcount
“I mean, what's interesting on AnswerBot, which is our product, one of our earlier customers was Dollar Shave Club. And actually what they did was, even though that they were freeing up time, even though that we are answering more, more solutions, they decided …”
Price: Over a third of Zendesk MRR comes from 100-agent accounts
“You know, our, I think over a third of our MRR now comes from customers with more than a hundred agents, and we are investing all the time in order to add capabilities within that area, but at the same time, keep the product super simple to deploy and configur…”
Price: Zendesk built AnswerBot in-house rather than acquiring AI startups
“Our machine, latest machine learning product, AnswerBot. We built ourselves you know, and you know, we have data scientists on staff, and because a lot of the work on that is how does it integrate, integrate very, very smoothly into the other products that you…”