some sort of events that drive returning and new is right.
- Yeah, yeah, exactly.
โYeah, you pretty much summed it up there.โ
The returning aspect is from the retention model that we have, the new customer revenue is from the, you know, the spending power model that we have. And then in terms of like the overall efficiencies and expectations within the month,
for those specific days, it all stems from, know, the emails, SMS, product launches, sales, promotions, things like that, that we are launching throughout the month. - Brands like Ridge, Ashley furniture, and Wayfair
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- Okay, and so it's the profit engineer or you, the person that's going in and running these models or is this something that's done by the data science team or the data team and they're, they're going and they're drumming up these models and they're saying,
hey, here's the optimal and jar go execute the inner, like what's your involvement in the creation of the plan and then the execution of the plan? - Yeah, yeah, it's a good question. As definitely an exercise, we have a great team of data
specialist in data, you know, engineers who put together
these models, first things, first it's just ingesting the data
and getting real clarity on everything and making sure that everything ingested directly in that, we have clarity and clarity there. And then from there, once we build off the models, it's essentially now we have the tools,
you know, to build out the forecast, minutes to profit engineers job to align with the team there on the client side, just see, you know, what actual goals we want to, you know, ladder up to, whether that's, you know, Max Revenue,
Max Lifetime, Cartribution margin, maybe we want to, you know, spend a certain amount within a specific month, you know, this is saving nuances there, but essentially, you know, getting the tool from the data team itself and then kind of,
art, but we're putting together a forecast, they stop, you know, alignment with the client.
Okay, so data in, data in kind of gives us some sort of baseline
of understanding of what might be possible, but it doesn't necessarily end there, it also, it also is a conversation in which,
โwhat is your goal, what is it that you're trying to accomplish?โ
Yeah, and then that gets, that gets put into the equation, and the combination of those two things then gets delivered, to jar or somebody like jar, and it's your job then to know what the daily expectation is, in order to ladder up to whatever their goal is,
and every single day you go out and you execute, towards that thing. Yep, completely, 100%. Okay, it seems simple enough, if I'm sitting on the, then the brand seed, I'm going, okay, great,
this sounds amazing. The, the thing that I do know is that like, when I was working with an agency, when I was running my brand, it's like midnight, and it's like two, four, and I'm sweating, and I'm like, uh, like,
the past four days are, are spend to revenues, been like 45% when the target's 30%. I'm sure, like, you're, you're just kind of, you know, watching some Netflix at 10 at night, and all of a sudden, somebody slacks you and goes,
hey, jar, we're missing the target for the day, what's, what's going on? So I'm assuming that those things happen all the time, but I'm guessing just like, my son, the other day, had a fire drill.
I'm assuming that you have some sort of technique, or some sort of like, plan whenever things don't go to plan. Is that, is that fair? Okay, so, so if I'm on the, if I'm on the brand side, and I'm saying, hey, jar, what's going on, dude?
We've, we've missed like two days, three days, four days in a row, you're told me that like day-to-day, we're gonna, we're gonna crush this. Like, what are you checking? What, what levers are you pulling?
What dials are you turning on?
โWhat are, what is it that you're trying to figure out?โ
Yeah, yeah, I think, you know, when a problem arises, number one is just diagnosing the issue. So stateless has a nice visual, like I said, like the hierarchy of metrics. So whether we're off in, you know,
contribution margin, whether we're off in, you know, overall volume, you can kind of bucket up like two problems, either in like volume, problem, or like an efficiency problem, and like the worst case is kind of like both, but just through that, looking at stateless,
you can see, you know, where you're off on the planet itself, because within stateless, they have, you know, the actual forecasted, numbers that we are supposed to hit versus the actuals. So we can see like the deltons and the percentages on a daily level, as well as like from, you know, weekly and monthly level as well.