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17 results for “growth metrics”
Concept8 mentions across episodes
growth
Topic2 mentions across episodes
metrics
Topic2 mentions across episodes
Growth metrics
That feels like a bit of an arbitrary number. If you can get it to 10,000,000 and it's super efficient and profitable, why is that bad? Because each business gonna be compared to flow. And when you have flow in the portfolio, which is, more than 75,0
11:12 / 12:16
from transcript11:12 – 12:16
...growth team or start a product led growth motion, is instrument product analytics, Amplitude, the Mixpanel, Pandl, so that you know what features you are using and connect that with the back end purchase data so that you have that usage and purchase
35:51 / 37:21
from transcript35:51 – 37:21
...gold on any growth metrics because you cannot goal it immediately, let's say, on monetization or immediately on acquisition. You're just gonna cut it at its at its knees immediately if you if you're not gonna let it evolve into something that can be
56:10 / 57:18
from transcript56:10 – 57:18
...metrics, setting up experiments, and writing custom queries. Or what if your growth team could get this time back? With Statasig, they can. Thousands of companies, from huge enterprises to start ups, rely on Statasig to ship faster, automate experime
49:27 / 50:53
from transcript49:27 – 50:53
...growth at some given time. And then later stage, they may focus on revenue because that's the bright moment to focus on that. So north star metric need to be reflecting your business objective, user getting value, but also your strategic direction. W
37:53 / 39:17
from transcript37:53 – 39:17
...on these metrics right now? And then you need to go through the exercise of, okay, well, if I move this part of the system from a to B, what happens to the output and how does that differ between if I move, you know, metric B from A to B. And what th
11:55 / 13:00
from transcript11:55 – 13:00
...metrics, setting up experiments, and writing custom queries. Or what if your growth team could get this time back? With Statasig, they can. Thousands of companies, from huge enterprises to start ups, rely on Statasig to ship faster, automate experime
2:08 / 3:42
from transcript2:08 – 3:42
...The metrics and the benchmarks, which are average and average commonly absolutely misleading, or the the benchmarks that you need to at least be looking at, but then, like, your product is different. How you even look at those metrics and benchmarks?
55:29 / 56:30
from transcript55:29 – 56:30
...is your core growth loop? Like all of these things. And then you can say, well, what are the metrics that we would use to measure that strategy and what would success look like? So that's number one. Number two is they basically go quant before qual.
35:50 / 37:02
from transcript35:50 – 37:02
and allow for more fuzzy attribution. So for example, we're going to be doing a big enterprise marketing push in San Francisco. We're doing billboards, we're doing podcasts, we're doing newsletters, we're doing events on the ground. And we're not goi
33:42 / 34:45
from transcript33:42 – 34:45
expand. I come in as an entry product and suddenly I'm using four or five. Does it really matter and can it not mislead you? Actually, the day to day metric and ratio we're really thinking out is CAC to payback period rather than CAC to LTV. We set d
35:56 / 37:43
from transcript35:56 – 37:43
...founders and growth teams on how to set the right metrics that you want to move? That's where I think the experimental design and the rigor of experiments comes in. You'll you'll have a hypothesis, and I think most marketers tend to jump to, let's go
9:44 / 10:47
from transcript9:44 – 10:47
...and growth teams on how to set the right metrics that you want to move?
8:58 / 10:07
from transcript8:58 – 10:07
...a growth model. Oftentimes, this starts by getting into a spreadsheet or actually pre spreadsheet. Write down how your product actually grows and how it should grow. So for Pinterest and there's a concept called the growth loops that maybe we could t
16:26 / 18:45
from transcript16:26 – 18:45
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