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20 results for “problem validation”
We saw so many customers coming to us with teams of data engineers that struggled with the manual work required to clean messy spreadsheets. File feeds two point o allows nontechnical teams to automate the process of transforming CSV and Excel files
39:44 / 40:45
from transcript39:44 – 40:45
“Customer success doesn't really have a strict definition. We can go to someone off the street and go tell me what sales does and they go, well, you ring up strangers and ask them for money. Everyone knows what that means. What does customer success do? I don't know. There's no definition.”
How does that influence your thinking when you start to think about customer success, I. E. What's core? Should should you absolutely always have? And then how do you think about what goes around that
20:35 / 21:06
Bold/Contrarian20:35 – 21:06
“People try to build a large enterprise style CS company into that kind of motion, and really what you should be doing there is customer marketing. You should lean in really heavily in product and customer marketing backed up by a smaller group of people.”
And the problems I see there are people try to build a large enterprise style CS company into that kind of motion, and really what you should be doing there is customer marketing. You should lean in r
22:59 / 23:16
Practical Framework22:59 – 23:16
...built validations and intelligent transforms. One schema helps you launch a guided CSV import experience in just thirty minutes. Get your customers to the value of your product in minutes and say goodbye to frustrating messages like import error onli
1:04:22 / 1:05:37
from transcript1:04:22 – 1:05:37
Cursor, Perplexity, Vercel, Plaid, and literally hundreds of other winning companies. So what are all these companies using WorkOS for? Imagine you're a fast growing startup. You've got product market fit, and you're getting inbound interest from big
1:44:14 / 1:45:20
from transcript1:44:14 – 1:45:20
Is this a p town kinda thing? I would because I'm married and have children. So the dweeb factor doesn't doesn't doesn't impact me. The thing that I'll say is I have in San Francisco, they've had earlier versions of these for some time, and they have
18:45 / 19:53
from transcript18:45 – 19:53
...pre built validations and intelligent transforms. One schema helps you launch a guided CSV import experience in just thirty minutes. Get your customers to the value of your product in minutes and say goodbye to frustrating messages like import error
1:25 / 2:40
from transcript1:25 – 2:40
...problems, and and you sort of create these, potentially, like typically, in my experience, I've seen about 10 to 15 clusters form of of very related problems. And the beauty of it is each of this bigger cluster, you actually know what the subproblems
32:59 / 34:09
from transcript32:59 – 34:09
But then they send you their security questionnaire. Yep. And it's, like, 47 pages long with requirements that kinda sound like alphabet soup. Do you support saml two dot o? Can you integrate with our Okta? Do you have SCIM provisioning, s c I m? Wha
1:18:00 / 1:19:02
from transcript1:18:00 – 1:19:02
...pre built validations and intelligent transforms. One schema helps you launch a guided CSV import experience in just thirty minutes. Get your customers to the value of your product in minutes and say goodbye to frustrating messages like import error
1:00:36 / 1:01:51
from transcript1:00:36 – 1:01:51
Puts a g word on their mouse? As a fellow boy scout, I I totally agree with you, but I wanna get Didi on. Let's get him. Sorry. We have him on the show. Didi Doss, if you don't know, he's an investor over at Minlo and he previously was a, software en
18:44 / 19:49
from transcript18:44 – 19:49
But to sell to those big buyers, you need to clear all of these compliance checks. You know that. That means you gotta have things like SOC two sorted out. What's SOC two? It's a standard and ensures that companies keep their customer data safe. And
20:12 / 21:16
from transcript20:12 – 21:16
...a built in validation layer that stops any bad data from entering your system, and OneSigma will notify your team immediately of any data that looks incorrect. I know that importing incorrect data can cause all kinds of pain for your customers and qu
46:26 / 47:30
from transcript46:26 – 47:30
...to to validate problems that they have. And we picked you know, funnily enough, I think most people don't know this, but we actually launched a mini app for finance that went viral very minorly on Twitter. What did it do? It was called, Fin. And what
21:42 / 22:52
from transcript21:42 – 22:52
...to problem validation to finding your customers and how to build the thing and get it in the market. For our first episode, I'm so excited to have Dion Nicholas here with us in the studio. He is the cofounder and chairman of forethought AI. Today for
0:00 / 1:24
from transcript0:00 – 1:24
...interviews, validation, discovery. What's the problem? Why doesn't it work? So I I'd say there's kinda two problems. One problem is that all of the books give you things that could work.
3:45 / 4:48
from transcript3:45 – 4:48
...interviews, validation, discovery. What's the problem? Why doesn't it work? So I I'd say there's kinda two problems. One problem is that all of the books give you things that could work. But that's the challenge. They could work, which implies that t
4:21 / 5:33
from transcript4:21 – 5:33
...problem for us, and we would pay a lot of money for this product once it gets to market.
20:13 / 21:20
from transcript20:13 – 21:20
...What's the problem you're going to solve? Now in most cases, you already validated that because you, you know, in the market for some years and you had dialogues with customers and you already realized that. And maybe you already told yourself, you k
1:05:15 / 1:06:21
from transcript1:05:15 – 1:06:21
...problems, external validation and recognition outside the company, etcetera, etcetera. I start off with that. I frame it in a very nonjudgmental way because I'd love to just start from a position of honesty and work with the incentives that are in pe
29:14 / 30:21
from transcript29:14 – 30:21
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