2026-03-12_brainforge_x_lmnt_1f00c395

Brainforge x LMNT

Date: March 12, 2026 Source: Granola Meeting ID: 1f00c395-c2bc-46aa-be74-fec17d83de1e URL: https://notes.granola.ai/t/1f00c395-c2bc-46aa-be74-fec17d83de1e

Participants:

• Uttam Kumaran (note creator) from Brainforge uttam@brainforge.ai
• Shivani shivani@drinklmnt.com
• Awaish Kumar from Brainforge awaish.kumar@brainforge.ai
• Jason jason@drinklmnt.com
• Ali ali@drinklmnt.com

---

LMNT 3PL Data Integration Challenge

• Ali from LMNT retail logistics team evaluating new 3PL partners for Target, Walmart, Costco fulfillment
• Current front-runner lacks API capability for lot-level inventory data extraction to Snowflake
• Alternative data transfer methods available:
  • Direct Snowflake data sharing
  • Email/SFTP CSV transfers
  • X12 documents using AS2 servers (EDI standard for fulfillment)
• Decision pending - will introduce Brainforge to chosen partner once selected
• Other candidate has API capability, less concern

Weekly Input/Output Planning Table

• Created week-by-week breakdown of data ingestion, modeling, and dashboard outputs for rest of year
• Covers Option B proposal scope with green highlighting for supply chain workstream additions
• Key timeline adjustments needed:
  • Spins access delayed to April 1st (move from March)
  • DSD from Encompass pushed to June (Jeff needs March-April setup time)
  • Retail Dashboard renamed from “VP Dashboard”
• Will present weekly updates aligned to this schedule
• Phil requested deeper weekly Gantt-style visibility into deliverables

Marketing Data Connections Status

• Jason clarifying which paid ad platforms actually in use vs historical
• Carlos/Kelsey confirmed not currently running: Adroll, Snapchat, TikTok, LinkedIn, Twitter, Pinterest, Criteo
• TikTok and Pinterest planned launch by end April
• Priority focus: Amazon marketing ads (beyond current Seller Central) and Bing
• Meta ads already connected, Google ads established
• Agency contacts facilitating Amazon and Bing access

Revenue vs Sales Definitions Framework

• Shivani developing comprehensive definitions with Jacob next week in Bozeman
• Key distinctions clarified:
  • Sales: What Element sells to wholesalers/retailers/end customers
  • Point of Sales: Consumer purchases at register (retail only)
  • Revenue variations: Net (sales minus discounts/refunds), Gross, Retail (includes chargebacks/trade spend)
• Geographic analysis complexity: POS data available for retail, but wholesale sales don’t map to specific locations
• Will create profit equation framework covering gross sales through COGS for all three channels

Omni Platform Pilot Scope

• Defined core stakeholder domains: wholesale, retail, ecom
• AI querying available for pilot testing now, broader team GA by April 21st
• Pilot questions focus on actionable insights per domain
• Out of scope items clearly documented for 4-6 week pilot timeline
• Training and adoption metrics tracking planned once dashboards live

Next Steps

• Uttam: Send input/output table to Phil by end of day with voiceover explanation
• Uttam: Provide 100-line CSV sample of stored inventory data for NetSuite integration requirements
• Jason: Continue Amazon marketing ads and Bing access coordination through agency contacts
• Shivani: Finalize revenue/sales definitions table with Jacob in Bozeman next week
• Team: Begin Omni pilot testing with AI querying capabilities

Transcript

Them: Hello. Me: Hello. Them: We got Ali Kamper in the house, okay? Let’s see. How you doing? Awaish. I’m good. How about you? Good. Hi, ali. Hi. Hi. I don’t know if you’ve met anybody from Brainforge before, have you? No, I haven’t. So thanks for having me today. Yeah. So Uttam is the CEO, co founder of Brainforge and Await is a data engineer on our team who’s been helping us model our data. More effectively, but I figured if you had an API data related question it would be good to not just have me answer. So curious. Should I kick it off? Yeah, go for it. I’m also not a tech person, so I’ll do my best to not what I’m about to try to say. Me: No problem. No problem. Them: So I guess just a quick intro. I lead our retail logistics and fulfillment team, so I work with our3PL to make sure product is getting out to Target, Walmart, Costco and we’re currently in the middle of an RFP choosing a new partner. And we’ve been inquiring with both of the new or the two front runners just around, of course, their tech and things like that. And not to get too into the weeds, but we won’t be doing lot code level tracking within NetSuite. And so we really want to make sure from an inventory data perspective. Me: Okay? Them: That we can pull inventory lot level data from these three PLs and get them get that level of detail into Snowflake. However, the 13 PL said that they don’t have API capability to pull that data over, and I wasn’t sure what other options there would be. If it’s not APIs, they’re like, is it going to be something super manual and annoying that should maybe be a flag for them, or just wanting to float it out there. Me: Yeah. Yeah. I think there are several other options. Them: Okay? Me: So I don’t know if you’re already on an email thread or how the conversation has been going, but I think I can certainly give you the blurb if you want to send that over. But typically there’s a couple of things you could do. Like one. They may not have API, but we have some of our other partners that are doing a direct. It’s called Direct Snowflake share of data. So there’s an option there. Also, if they’re able to send us even email or SFT data in as a CSV, we can capture that. Them: Yeah. Me: So it’s sort of for us assessing. One other good way is like, hey, I know you guys don’t have an API. How are some of your other customers absorbing data from Xtool? Is another way of getting them to share. If there are other methods. Those are some of the more common ways. So if it’s helpful. Them: Yeah. Okay? Me: We can give you a blurb. Or you could throw me into. There’s an email. Happy to coordinate. Whatever. Them: Yeah. Let me. I mean, it’s. It’s hopeful to me that you are at least saying, like, yeah, there’s absolutely other ways to do this. Me: We’ll see. I can’t speak. Them: Here’s what they told me. This is. This is my note that I wrote down. And it essentially feels like a foreign language. They said something about X12 documents using AS2 servers. No idea what that means, but what I was going to say is that we’re very close to choosing the partner, and so maybe I will loop you in with them. Once we choose, you know, once we know which one we’re going with, the other one is API capable, so I’m not as I don’t. Have as many questions around them. Me: Okay? Okay? O. Kay. O. Kay. Yeah. If it is a deciding factor in the decision, then it’s certainly important to just. Let’s map it out. I’m familiar. I just googled AS two. Yeah, it’s like threw this thing called edi, which is pretty common in fulfillment for data transfer. Them: Y. Eah. Yeah. Me: So, yeah, I would basically just need, like, a little bit more documentation for them to sort of give you the super solid. Yes. No. Them: Okay? Okay. Maybe I will link you up with them just to like. Because I think it’s. We’re leaning more towards that partner who doesn’t have there. And they’re looking to have API just. It probably won’t be until like next year sometime. Me: Okay? Okay? Okay? Them: So would love to know, like, your thoughts, so I’ll maybe I’ll just make a little intro via email and. Me: Sure. Them: Ali like, the one thing on this, like, introducing to Brainforge is it’s just getting a lot like if, if it’s too many cooks in the kitchen, like, sometimes feel like I’m like, oh, Uttam is going to email spins to figure out what the API access is and entails, and he was like, that should be an element conversation with Spin. So it’s still a little bit like, I think some people are kind of like, there should be us talking to them. Yeah. Like, Uttam also offered to draft emails to send to our retailers because while we get data from Emerson, like for Target and Walmart, we don’t necessarily have point of sales data, like, coming in in an easy way. For Vitamin Shop, it’s like, oh, like, there are spreadsheets that we get sent once a week. Like, how do we actually make this more seamless? And so Will was kind of like, let me have the conversation with a retailer. So I’m just sharing all that context in the sense that, like, we can. Why don’t we send you a blurb, and then if you’re like, this is just a foreign language for me, I’ll put you in a group chat with Uttam and, you know, whatever, Jason with them or something. And then he can draft something, and then let’s see how it goes. And if you’re like, at some point after that, you’re like, I just really need Brainforge to talk to them. And, like, nailed us down. And then we can. That’s great. Yes. That’s great. I’m. Like, obviously not familiar with the. The current workings here. So, yeah, if you want to draft something up for me, then I can send it over. And let you know. I’ve just noticed it. I kind of am like, let’s just get with them in the mix. And then I’ve noticed sometimes people are like, no, that’s for us to handle. Me: Yeah, I’m here working for y’all. So you use us however you tell me. Them: Something like that’s for us to handle. So I’m just trying to read the. I’m trying to figure out the protocol here. Yeah, but I put a group chat together, and then he can draft something for you, and then if it makes sense, bring him in the conversation. Let’s do that. Me: Yeah, yeah. Them: Okay? Sounds great. Awesome. Thank you. Thank you, guys. That’s all I needed. So I will. I will let you have the rest of this meeting. Me: Thank you. Them: Thank you. Bye. It was nice to meet you. Me: By. Okay? Great. Them: Jason, are you doing okay? Yeah. No, you weren’t feeling well last week, so then I was like. I was like, are you. Are you. No, I’m still. Ill from that perspective, like Nicole. But mentally, I’m feeling okay. Okay. Gotcha. Yeah, Good. Okay, so. Uttam. You want to share other agenda topics. Me: Yes. So I can just share screen. Cool. So I like seeing this every week. It’s very helpful for me. But in terms of agenda, I think these are the core things that we want to do this nicely. 10 minutes seems like we got this done. And then today, I think the three core things I want to review are like sort of our input output stable for the rest of the year in terms of our proposal. Them: Yes. Me: I want to talk a little bit about some of the revenue versus sales definitions, and we can look at the metrics table and sort of talk through how we want to find some of those. And then I want to talk about the Omniplan. So we have sort of what we talked about yesterday, which is we’re going to take a first pass. Like what each stakeholder cares about, like what we think is in and out of the pilot. Them: Omniplan. Me: We have a version of that. We can walk through. And then I have updates on ingestions, models that we can get into if we have time, but it’s all kind of in the deck. So. Them: That sounds good. On on the one note on the revenue versus sales definition that added that because actually did a converse I had a conversation with people on finance, so I want to. That’s more like me sharing. It’s not complete, but it’s like sharing something and I think it like kind of. Me: Oh, great. Okay. Oh, perfect. Them: Tease. It bleeds into the Omni conversation, I guess, because it’s like. Me: Okay? Them: Like, it’s like what’s actually in scope for Omni? And what can we answer realistically? Me: Do you want to start with omni thing? Before to see how we’re kind of like. Whatever. Either way. Them: Either way, I think let’s. Let’s do the inputs. Output state. That one feels like the big one. Yeah. Me: Okay? O. Kay. Them: So inputs, outputs, table. Jason, is what I alluded to about, like, what Phil was asking for of, like, weekly Gantt. It was a deeper level of like, what’s happening? Tweak, tweak. You can see I just hid a couple columns. I didn’t delete them. Me: In this. Them: You know? Yeah. Yeah, I just hid. I just hid them just so that I could have, like, two things I was looking at, ok? Me: Okay? Okay, okay. Them: Ay. And I think this will be a good, good fodder for us. Me: Yeah. So to orient on this. This sheet. So basically, we heard the feedback and we wanted to break down by a week what were the things that were entering the system. What are the things that are currently being modeled. And then what is coming out in the form of dashboards, analyses, like capabilities. Right. So it’s sort of similar to the Gantt view, except more about, like, it’s less about how they’re tied to the inputs, more about us week by week. What we’re trying to nail one thing at the front of this document is we just had, like, a little bit of, like. Okay, here are some of the deliverables. And then here are some of the, like, one sentence, like, what this is. So a lot of these are self explanatory, but for some things like for example, we, we have to, we may have to like bring a bunch of people together to start confirming metrics. Like this is our terminology for that doesn’t really make sense. You may not see that standing alone. So we kind of put some definitions here. The options align with each of our proposals. But I think just to focus on option B, what you’re seeing here is like what is being ingested and then what is the dashboard or reporting unlock that is coming out? What’s highlighted in green is sort of some, some pieces of the green are going to be additional related to the supply chain work stream. So I’ve highlighted sort of just these cells in green. And I know you hit this sort of modeling QA piece, but I think this is. This is simple. Them: Yeah. Me: Of course. Like, I think I’ll just do last piece in terms and then kind of can get feedback. What you’ll see in the way we present the deck today is actually going to be sort of aligned with this. Which is, I think about this as, like, the supply chain of, like, the data team. So what are things that are being ingested? What are things that are being modeled at any moment and like, how are we enabling reporting or analysis outcomes? I think this is probably the most, like, wishy washy. Meaning, like, we may find that we want to go deeper in some area. Based on what the modeling unlocks, but based on r what we’ve heard. I would say we’re fairly accurate. Additionally, you’ll see that there’s pieces about Omni all throughout, like March, April. As we’re, like, getting the BI tools set up, and then we will be using the tool for these dashboards, you know, coming up. And then as new requirements come in, like they get slotted. So, like to wrap that about, we’ll be presenting on a weekly basis as aligned to this sheet as possible. And, you know, we can still maintain the Gantt, but ideally, we want to say, like this ingestion piece was delayed. So it’s moving to next week. This modeling expanded due to some, like, unforeseen thing, or we had an additional dashboard requirement that we approved. And so I think this is another form of, like, looking at that sort of what is the week by week plan for the rest of the year for us? Them: Great. In terms of what you want to. Now that you’ve walked us through the orientation of, like, what this has before, we, like, share this with Phil and we say, like, okay, they gave us the thing that you were kind of, like, asking for. Me: Sure. Them: Are there any call outs? Are there any places you’re looking for feedback or input? Like, already I kind of see. Oh, no, that says stripe. Sorry. My. I thought that said spittance. I just read it wrong. Me: Yeah. So we put spins just later here. Them: Where is. Me: I put spins, sort of like end of this month. Them: Already, they said earlier. Since April 1st or something, so, like, I would just punt that. So you’re not, like, already behind on your schedule? Me: Okay? Them: Because they’re, like, the earliest we can get you that access is April 1st. I don’t know why they would say that, but then let’s just put it for April and then. Sorry. I started with a macro question, then I drove. I went into, like, specific feedback. What do you. Me: Yeah, you said, like, is there anything we want to drill into? Them: Yes. Is there? Me: Yeah. Yeah, go ahead, jason. Them: No question. Me: Okay? Them: Like, can I One other thing, because I’m just, like. I want to be able to ship this, like, soon. So that’s why I’m just, like, doing light edits right now. Me: Please. Sure, sure, sure. Please. Please. Yeah. Yeah. I went through line by line. There is a lot. So I would love another set of eyes to just, like, look through pieces. Of course, like, we. I’m trying to estimate the best that, like, we’re going to start to get things. So like. You’ll see confido. You may see atomic. Those are things that they just had to end up here. We could either be more, like, conservative with it and just move them later. But this does encompass all of the currently aware, like sources that, that we’ve listed. Them: Okay? Me: On this. Them: So. DSD from Encompass ingestion. I’d say I talked to Jeff and he’s like, I need more time to make sure that I’m configuring in compass in a way that makes sense to me. And he’s like, so. So let’s say I have March and April sprints to do that. He’s like, I don’t want to think about it, going to another place until I do that. So he was like, I would put June. He’s like, give me time because it’s such a new thing. And he’s like trying to figure out how does he configure. Me: Yeah. Yeah, it’s a whole setup of that thing. Them: The whole setup. Yeah. Of like, his pnl, basically. Right. Okay, so dsd. Great. Move that to June where it says retail vp, Dashboard Live. I’m just being. You do anything wrong there? Is that the fill dashboard that we made? Me: Yeah. Yeah. Sure. Yeah. Them: So let’s just change the language there to say. Retail dashboard life, actually, because we. We’re in the midst of trying to hire vp, and then it’s just that that’s easier. Me: Okay. Okay. So, like, yeah, there’s some things around. Don’t. I don’t know if there’s. Let me just see if there’s any other VP thing. Yeah, that’s actually it. Them: Okay, cool. Where it said vp dashboard live. Or, sorry, the retail dashboard live. Me: Yeah. Them: Is that like qa is, then qa is done on that. Me: So. Yeah. So this is going to be. I mean, partly this bleeds into, like, what we’re going to confirm as the Omni plan. But ultimately, one angle of looking at the plan is I would like to replicate as much as in Google sheets, Into Omni that exists today. Them: Yeah. Me: Again. Right now we just have this spreadsheet view. So it may be that. It may be graphs, but that is in scope for this first piece. To basically enable because it’s really easy for us to look at that apples to apples. Compare functionality, things like that. So we can talk about live different than is this being shared? Is this being shared out? I think is maybe something we have to talk about. The phasing we, of course, review between you, Jason, Dan, and then how does it sort of permeate through the org for some of these. Them: So. Yeah. Me: It’s sort of like where in April we have this. The way we’ve kind of paced it is like, by mid April, there’ll be a guide on, like, how to use Omni. We can start doing individual team, like, training. And so it’s really clear when you go to Omni home, like, where to go all of that stuff. This group will have awareness of a lot of that very early on. So this is more about the rest of the element or, like, starting to onboard? And being able to use AI features, things like that. Them: Gotcha. Me: It’s not. Not related to the pilot, necessarily. Them: Okay, look, I know sometimes I end up sprinkling and, like, kind of feedback at the same time, but, like. Like, you know, I’m like, why are there zeros for target inventory? Everybody wants to talk about inventory, but it’s literally zeros. And people seem to be wanting to QA it, but isn’t. It obvious that it’s, like, wrong in some capacity? So that’s just like, when I say, like, what is the process of qa? I’m like, still a little. You know, everyone’s like, so what is the Brainforge process for QA versus me needing to read it, which is fine. Me: Sure. Yeah. Yeah, but. Them: But I’m like, I don’t know what Retail Dashboard Live is. Is like, we’ve checked the box with, you know, I’m just trying to figure out. Me: Sure. Them: I guess there is meta question around what is live and what is being fed. If we have. Me: Yeah. I mean, so there’s, like, also a couple of things where, like, we’re learning through the whole process. How often do DBT models need to run? How often is polyatomic run? We found today that Emerson actually just. It’s like we. We actually stopped getting data from Emerson, like, two days ago. So then I’m like, okay, we need to investigate that. So these are all, like, live investigations. So part of, like, what I’m going to start to present on is more on, like, observability and, like, accuracy. We are always going to have these. Like, I, I can’t say that there’s never going to be data issues. It’s going to be more about, like, our speed to remedy them and triage them. So we are queuing as much as we can. Them: Great. Yeah. Me: I think we’re also just building, like, the core platform. So we weren’t aware that there was going to be, like, a delay in Emerson, which then the same, same day last week thing didn’t work. Them: Yeah. That happened before, too. I remember, Jason, that Emerson just sort of was like, we’re on pause. Me: So. So for me, we need to have some alerting. But again, a lot of that when we do Omni, we will show pieces about like, okay, what is the adoption? Like who’s using what but then also alerting. Hey, this thing is delayed. Hey, this thing is totally off. So that’s sort of what the next. Month is going to be. It’s hard to do that in a Google Sheets like environment right now. But I hear you. Them: Okay, cool. Me: So we are doing. We are going to do QA both, like our typical, which is like, we’re doing code reviews and things like that. And then we will do some QA with a business. Similar to how we want with Bass. We’ll do similar things with. With Laura, and we’ll go through sort of each of the teams. Them: Yeah. Another. Oh, sorry, another question. Me: No, no. So I think that’s, that’s like the wrap on, like, the QA piece, like, how we’re going to do that. And then ultimately people should have expectations, like, okay. This data is only going to be of like close the business yesterday. And so, like, some of that is all going to be. It’s going to be a lot of training. And then again, I just want to, like, caveat. Like, things are going to. Even as hard as we try, there will be times where, like, something doesn’t load or it’s just our speed to fix. Them: Of course. Yeah. Another question I have is, like, you know, I was surprised when I saw AI querying Live in Omni. More so because I was like, I thought we were piloting it for a month. And that AI querying would be a part of my pilot. So I was like, at what point do I put hands to keyboard and just start querying the data? But is that I don’t. I don’t necessarily. We’ll get into omni as a double click later. But, like, I don’t know if I necessarily understand. Like, if I were to really lay out for the business, what does the omnipotent mean? Like, if I’m supposed to say, yes or no on a BI tool. I want to know what’s in scope or out of scope or, like, at what point I’m supposed to be impressed by the AI future. So I was like, oh, I won’t be able to use AI like querying until April 21st. Me: Yeah. Yeah, I guess you’re right. So in this situation, we could. We could have said. Pilot versus, like, go live. Them: Yeah. Me: You will be able to use. You could use the AI Thing right now. Them: Okay? Me: And we it just is going to take like this amount of time to like, harden it and then to release it to, like, be comfortable releasing it to any user at element. Them: I see. It’s like, I might pilot it, and then it’ll be like, no, we don’t have that. No, we don’t have that. Me: Yeah. Within the next month, we’re going to show you as much an omni as possible. Them: Okay, okay. Me: As well as with, like, hey, this is like 50% there, but you’re gonna be like, you’ll be able to use the AI all of these dashboards. Them: Yeah. Me: Is gonna be associated with also having AI just alongside of it. But you’ll also recognize that there’s still more context we need to add and like some tuning that’s just gonna take longer. So I can rename this to just like AI Querying Live for broader element team. Them: Okay, perfect. I love that. Yeah, that. That was. I was like. I was a pilot user. I’m not going to be able to use AI until April 21, and I thought there was no point. Okay? Jason, do you have any thoughts on this? Like, I. Like, I. I know I shared with you a little bit around, like. Like what Phil was looking for. He’s like, hey, if we’re going to be paying a lot more to Brainforge, I want to understand, like, what am I getting? And when, like, do you think that this sort of meets that? I think at a high level. Yes. I mean, I think we’re. Thinking about it kind of in verbiage now, right, so. Yeah, I think. You made a good point, Shivani. Where it’s like there’s. There’s like, a testing period, and then there’s, like, a general availability period. Right. Me: Yeah, right. GA is probably the better term. Yeah. Them: Yeah. So, like, I feel like we might need to kind of, like, circle in those terms there, because up to, like, you’re right. It’s like no data connection is going to be, like, 100% up all the time, and things will fail. So I think it might be why it’s incorporate. Like, hey, it’s like, we’re up. It’s beta, or, you know, you know, whatever we want to call it. And then it’s like, at this point here, we feel like it’d be GA for the rest of the group, I think. That generally kind of what I’m sensing. Me: Okay? O. Kay. Them: When Shivani, like, asking those questions around, you know, what does that mean when it’s like, live or cue anything? And I think Shivani, though, it is important for us to kind of communicate, though, to, like, feel like. Like, when we go through some of these things right here, like, if your expectation is. Before I hand it to Phil, that the data has been validated by, like, each of the internal teams. Then we would need to kind of call that out as like a phase then. So he’s aware of that, that, that that part needs to be done, or if that’s your expectation, as far as what live means or gnc. Right. And so it’s like, I think, a side note or like, or we just. Me: Yeah, I can just think about putting it here. From ingestion to model to, like, a dashboard. I mean, again, to make it clear, like, we’re gonna review. Then it’s like the core data platform team. Like, whatever, the core stakeholder, and then it goes ga. Them: It feels like a, like, slide adjacent to this. That’s like, hey, like, by the way, this is like, the typical flow, which goes from ingestion to modeling to QA to, like. Like, there’s QA throughout. Like, you could even have that be a separate bar. There’s QA throughout. Although this. Me: Wow. No. So there is cross cutting. It’s like all the maintenance. There’s like a bunch of cross cutting things that we’re just always observing and doing. Them: Sure. And it’s like, element QA is always but, sorry, sorry, Brainforge. QA is like throughout, but then Element QA is like a period of time where it’s meant for you. And between element QA, it goes from being V1 to being live. Like element has qa. It’s alive. And then we figure out what is general access to this require, which might be, like, education about the dashboard. It might be like, you know, there might be, like, other things before we start socializing dashboards to people. Me: Yeah. Them: Yeah. So, Shivani, would it help then? If there’s a sense of. There’s QA from an integration perspective, right? To say, like, the connector works. All the data is flowing. It all is good. And then there’s a period of qa. Where we need a stakeholder to look at it to kind of like, provide that feedback. Would you want? Like, would you be okay calling that like, please keep me honest here? Like, would you be okay calling that, like, kind of like a beta phase, if you will? Like, hey, this is, like, for Alpha, right? Me: Yeah. Them: Meaning all the connections are all there, but we need someone to start playing with reports of validated. Right. But you’re playing with live data. Right. So it’s not like a test data thing. Right. So if it works, it works. But if something is off, this is the time to, like, correct it. You know, before we say, hey, this is. Now a ga, which then comes into, like, regular kind of like, maintenance mode, right? At that point, when something goes down or, you know, A new field would add. And then we just kind of have to add that as, you know, as I comes. Me: Yeah. I mean, in the past, it’s common to do, like, okay, this thing is after modeling, it’s in, like, internal qa, it’s in, like, external qa, then it’s made available. And then, typically, the way we will actually project it out is from the dashboard backwards. So like a dashboard. Will include making sure the ingestion works, getting the models done. The internal. Like that. Basically the dashboard design. Internal qa. External qa. And then it’s sort of like it exists. It’s not like we don’t talk about it. And then it start. So there’s. It’s like just for how we phase it. That’s the way we are going. To do it. I think you’re already seeing for, like, for wholesale. For example, we basically went. Went through that. And then it sort of cycles in between external, internal QA until everybody’s happy. That’s the one piece that’s hard to predict. Them: Of course. Yeah. And that’s what I’m hoping the internal hire can, like, own that. Me: But yes. Yeah, because you can see, it can take like. Like, we’ll. We’ll call it best tomorrow. But it could take these, like, cycles of like. Okay, we push the fix now. Let’s track and let’s do it. Them: Yeah, it’s like, oh, I forgot that I wanted discounts. And it’s like, okay, like. Like, the scope changes a little bit. Oh, I thought I actually wanted the fourth order instead of the third order. Like, made a mistake. Me: Yeah. Yeah. Them: So. So. Me: So, like, if it’s helpful, we can. I can create a little diagram that’s, like, how it flows and then just kind of loop between internal qa, external qa. There is some sense of, like, versioning of these dashboards as well. For example, like, we may push out something like a set of dashboards for wholesale, come back, make a series of improvements, call it V2. But that’s a little bit playing with just semantics on how we want to do, because we’re always going to be improving, right? It’s not as like we’re it’s not like in software. You do, like, releases. It’s not as. Because we’re just always going to be like, hey, I need a field. And we’re not going to just wait to, like, release that. So in that sense, maybe we do this loop between internal, external. If you want to do one more phase, which is like, okay, it just starts with that team versus, like, being made available to the whole company. Them: Rry. Me: We could add that. Them: And you don’t. This is not even for, like. This is not necessarily for, like, this thing. This is like almost, I feel like a tangential conversation around, like, how do we start educating people at element about what this data project entails? Me: Totally. Yeah. Them: What is a data table? What is the flow of qa? Like? What’s. What’s the. What’s the process and journey look like for you to get insights from your data? Right. Which is like a deck. I’m kind of, like, desiring delivering to people internally. Me: Yeah. Yeah. Them: And so I think, like, I think for this exercise, what you’ve done is fine. Me: Okay? Them: And then we can caveat it with. With Phil. That’s like. Like, maybe we just remove the word live and we just say, like, cross channel omni dashboard, like, whatever. Me: Okay? Okay? Them: You know, or just. Or just call it a V1, right. With an understanding that this is going to. It’s going to be ever evolving, right? And at some point, once Omni is, like, totally adopted, with Omni Shivani, like, there will no longer be dashboards because everybody should be creating themselves, frankly. Me: Yeah. Yeah. Them: Right. Me: So. So that’s kind of what we’re hoping is, like, by this point, at least, we have some people that have adopted naturally, will find who are, like, the real power users that can start to build. That would be. That’s, like the best, super best case scenario, you know? So I think I can just say, like, so is the kind of thinking here. Just. Put. I forgot what we call kind of a ride back. Do we say, like, we want. You want to do live? Do we just do V1? We could do ga. I think maybe two questions. Do we want it, like, I could just say, like, yeah, V1, and then do you want me to also list retail dashboard element qa? Them: V1. Just put v1. No. Me: Okay? Them: No, not for this. And then. Me: Ok? Ay. And so part some things you’re going to see here is also like, like this data quality scorecard, because at this point, we will have consumers. So then it’s important that when we present to you weekly, we’ll start to show you not only adoption. Okay, how many queries are being run? Who’s querying what? But also, like, what were the data issues this week? Okay. Something was delayed. Them: Yeah. Me: A model broke. Something like the call was missing. So this is a. This is at the point where we’re kind of like, okay, people are going to be. People are. Right now, I think people are going to be end to end using something that the data platform team produced. Them: Yes. Me: And now we’re maintaining that. And I think it’s not oftentimes that the data team is not only just, like, protecting, hey, everything’s working, but also showing that things are getting adopted. So I think that’s one thing that we’ll start to share. And Omnia is a really great view of showing, like here’s a queries, when are they happening? What are people using AI for? And things like that. Them: Okay. This is great. I think this looks good. Uttam. I think. I think that, to me, this feels like something I would feel comfortable sharing with Phil. I don’t love the word salad at the bottom with all the like. Can you scroll down? Me: This, okay? Them: I don’t think that’s needed in this, like, like. Me: It’s on. It’s. It’s here. So I was just. Them: Okay. Like, I. I think really it’s just sharing. It’s making a copy of option B tab. It’s saying this is what you’d get. Like. Like, I think Phil is kind of leaning towards option B in the sense that he’s like, if we’re going to do this, like, why would we pay option 8? Like, if it ends earlier, it ends earlier. Like, but let’s, like, do it and then be done to some extent. Me: Check. Yeah. Them: So if he’s like, let’s go for option B. And then let’s say that that’s April, May, June, July. And then we, like, taper down or something, right? Like, that’s kind of. Me: Okay? Them: Like there’s some version of that that we can, like, voiceover versus, like, option B continues through the end of time. No way, right? Me: Yeah. Them: And so I think that this feels comfortable. If there’s a voiceover you want to give, like, yes, you can change the word live to V1 or whatever you want to do. But if there’s a voiceover you want to give, which. Like. On some of the pieces, then maybe you could make a little loom. But, like, I don’t. I think my goal is to get this in his hands, like. Me: Okay? It’ll basically be what I said in the start of this. So if that was, like, I can do that, that’s fine. Them: I like what you just said, which is like, hey, like, we want to talk about. We want to, like, share with you, like, how this is actually being adopted and, like, be your partners and, like, not only just the delivery of these models, but actually the adoption of these models. Me: Sure. Them: And. And, like, I think that’s just nice. I liked that. So. Or. Or that could be in your email. Me: Okay? Okay? Them: Or something, okay? Me: Cool. Them: But I think otherwise. It’s like he might have questions, and if he does, then I’m going to say, like, if he’s kind of like, what can I answer right now? Guide what? What is that about? Like, if he’s like, what does that mean? Then I’ll say, like, why don’t we just set up? Like, instead of playing telephone, why don’t we just 20 minutes without them, okay? Me: Y. Eah. Yeah. Yeah. I mean, look, I think the clear goal is, like, anything that will be reported on whether within this phase or not, we want to get right. By here. Them: Yeah. Me: Let’s see. Like I’m expecting retail to take longer. We don’t know if I can fido some of these, but this is all of it. I think, Jason, for your clarity as well. Like this is how we’re moving. We n use all of these sources. Directly, immediately. But actually, a lot of these are going to allow us to get a full picture marketing spend of retail revenue. Which without some of these, like, if we were to paste this out slower, It would prevent us from sort of giving the full picture to do things like all of our spend, all of our revenue. Looking at efficiency by channel, things like that. If there are sources that, like, for example, if we find that there’s a source where it doesn’t necessarily affect the ultimate goal, and it’s a nice to have. Then we’ll have a discussion on like, this is a P3. This is like a nice to have just to get. Them: Like a non digital marketing that we talked about, right? Which is like field marketing or something. Yeah. Me: Yeah. Yeah. And so it’s like there’s no existing reporting on this. It’s some tool that someone’s using. We can ingest it now or schedule for later. And we’re expecting. Them: And it’s probably that some of those things just hit QuickBooks. But don’t necessarily like. Me: The spend will, but QuickBooks may not have a granularity of like what campaign it was spent on. How many impressions did it get? Them: Yeah. Me: And this is like, one of the things about marketing is, like, they will adopt new tools. By the time we get to June. It will just be up to us to say, like, is this relevant enough to do? Is it even part of the OKRs we’re trying to support? And, like, just keep trying to drive towards the commercial side, having clear understanding of these. Them: One thing that like, I like the. Mayor Finalized. Like marketing efficiency, still finalized. Me: Yeah. Them: Like, one thing that’s coming to my mind is, like, Maybe the segues into the. Let me see if the segues into the revenue conversation. Yeah, I guess. You like? I don’t want. When I see Cross Channel Omni Dashboard Live, I’m like, that’s good. But, like, what does that actually entail? So I think let’s. I feel good about this table. Me: Okay? Okay. Yeah. Because we’re just going to get into requirements. Okay? Yeah. Them: Yeah. Me: Great. Them: Okay. Jason, do you have any other thoughts on the table? Me: Sure. Them: I’ve got a couple comments regarding kind of the open item that we had around the marketing connections that are still open. Me: Yeah. Them: That I’m working through. So I’m going to take a little bit of a tangent here. I spoke to Carl, I spoke to Carlos and Kelsey about these, actually. Me: Please. Them: Because this is where I going to need their support to like getting access to these systems here. And the list that was provided was like ad role, Bing ad, Snapchat, TikTok, all this stuff. Me: Yeah. Them: I’m curious. Is this a generalist, or was this defined by Carlos or Kelsey? Because they actually came back to me. And they said, we’re not running any paid ads. With adroll, snapchat, TikTok, LinkedIn, twitter, pinterest or critio right now. They do plan on launching TikTok and Pinterest by the end of April. Me: Yeah, waste time. Them: Okay? We got the list from, like. What? We spoke with the Carlos Plus. Also we had a metrics dictionary. From the source medium, which. The dashboard. Which Karlos was using. Okay. It’s not the references from both. We actually call these sources. Me: Yeah. So if they had ever used these to spend, it would be valid. Them: Right. Me: So ultimately, it’s like, yes, they may not be spending through that channel now, but I would say if they spent on in the last two years, It’s relevant for us to. To have. Them: Okay? Me: So. And some of these, again, are as much as we just have to put the keys in. So there shouldn’t be any. All that we’ve sourced from our initial discovery. On either from source medium or from speaking with with Carlos. Them: Okay, got it. I think there’s some confusion, then, about how I’m supposed to, like, get some of this info. Because, like, Carlos is now deferring me to, like, the ad agencies that they’re working with. To try and get access to some of this stuff because I think it’s been such a long time. Me: Okay? Them: For some of them that we haven’t. Used them in a while. Me: Okay? Them: But the ones that I’m focusing right now are Bing and then Amazon. So for Amazon specifically, we’re, we’re connected right now to Seller central, but it’s the marketing ads that we still need to get connected to, is that correct? Me: Yeah. Correct. Them: Okay? Cool. I’ve got connections, or I’ve been connected with their agency contact that is helping to kind of facilitate those two. Me: Okay? Okay? Them: Right now. So, being an Amazon. The other ones, though, I. I’ve still got to research about how we’re supposed to get this information, Yeah. Me: Okay? Okay? Them: Because I think there. I think because we don’t have anything current on it. Like, honestly, there’s a lot of. Not a lot of knowledge in terms of, like, how to get that now. So there are pointers on where to get this done. Let me know. Otherwise, I’m going to work with the ad agents now on this stuff. Me: Okay, okay. Yeah, it’s. It’s not uncommon. For them. To just be spending across this many channels. And I’m not surprised if they turned it on at one point and turned it off. Them: Like hearing one thing, but. Me: Though the sources that we already have and the ones you listed, like Amazon, we also have Meta and Bing are commonly going to be the biggest ones. So of course, like, if I had to prioritize, I want to get the channels with the most spend that has been spent in the last six months. Them: Y. Eah. Right. Me: But ultimately. Them: Have we connected? I’m sorry. Just make sure. You’re making sure how we connected. To meta ads already since that wasn’t on the list. Okay. Me: Yes. Yeah. Them: So we just see the Amazon one and the big one. As far as the top three. Me: Yes. From my understanding of, like, where most of the spend is. Them: Okay? Me: That’s correct. And then for the rest again. I think it’s like, we will end up coming back down the road if we QA and we find, like, hey, There’s a month from like a year ago where the OKRs and like this, though, doesn’t match. We’ll end up coming back and saying, like, oh, it’s because we spent. We had a month where we spent 30k on. On kritia or something, or Adroll. So that’s why they’re listed all as P2. If you. If you prefer, I can even go one step further. Like I know some of these are actually going to be way smaller. Just knowing the business, so I can even. We can go another layer. And you just tell me, kind of like what. What you feel like is best for capacity. Because I also don’t want you to go chase. Them: No. Well, yeah, if you have the. And that’s quick, great. But I think just right now, like, just having this conversation. So I’m chasing after the big one. I’m chasing after the Amazon one. Me: Okay? Them: And then everything else kind of is a P2 compared to those. Me: Yeah, like, we already got Google Ads, Facebook ads. Those are going to be, like, super major. And then yeah being an Amazon are going to be also really important. I don’t we have listed like LinkedIn, Twitter but I TikTok I guess I heard yeah if it’s not already being used. That will be the next one for us to go after. Them: Y. Me: It’s usually what we see. Them: Okay? Cool. That helps with the clarity I need. Me: Okay? Them: Appreciate that. Thanks. Me: Perfect. And then we, yeah, we kicked off Amazon, sort of waiting for, I think. Gala was going back and forth. On walmart with steve. About an entity key and getting app approved. So they’re still going on there. So we’ll just keep kicking off, you know, as many of these. As possible. I do want to make sure that we go through Omni Plan Shivani, so maybe I’ll pull that up. And then can we talk about the revenue sales definitions? And, like, have that discussion. That would be great. So to kind of, like, set the stage on, like, what we wrote here, we basically listed some of the core element domains that we’re trying to hit first. And really, the way we’ve outlined this is, like, who are the core stakeholders? Some lists for our team on, like, what is some of the pilot data? And then the questions we’re trying to answer in the pilot. I think similarly, like, during our conversation with Greg is like, what is a home run? Is if we’re like these questions, you can now answer. These are questions that we heard or basically inferred from a lot of our discovery. As well as, like, making sure the AI is working. Above and beyond like what’s listed here. We’ve also listed kind of like what is out of scope. And so this is. These are things that I would say out of scope. Just to hit, like what we’re trying to nail next four to six weeks. And so we’ve done this for wholesale, for retail. And then we. We are modeling ecom. I basically kind of wrote that if we can get stuff in there, I think we try to. But these are the three, like, core areas we’re. We’re trying to hit right now and enable the entire Omni platform. That’s just this part of the doc. Them: This looks good to me. Me: Okay? So maybe we can talk about the sales revenue piece. Them: Yeah. Let me pull that up. So. Okay? This is just like, you know, I’ve been saying this maybe before I even share my screen so we don’t get distracted. You know, I’ve been saying repeatedly, what if I’m an executive who, like, wants to see how I. Like, okay, Jeff Warren, right now, head of distribution, he’s trying to look at, like, certain cues to say what city should he next tackle for self distribution. Me: Yeah. Them: Okay. And so what he’s doing is he’s, like, trying to look at wholesale data, target point of sales data, and wholesale, like, target point of sales and. I don’t know what else. Right. Like, he’s just trying to look at a couple proxies to say, like, okay, where are we? Wholesale numbers, target and then market sizes, density, number of stores, whatever to help us figure out where DSD should go. So let’s say he’s the stakeholder. Me: Okay? Them: Then what I was thinking about is like, what if I just want to know how point of sales were across California, across my channels? Well, that doesn’t really work. Ok, because point of sales data. Where do I have point of sales data? Just retail. Me: Yes. Them: I don’t have point of sales data for wholesale. Like, I don’t know how that works. And, like, I think I needed to crystallize this for myself. It might be obvious to some people in the business, but I was like, if I was trying to query something in what I kept getting stuck on is if I’m trying to query something across channel, like what is actually possible. Me: Yeah. Yes, yes. Them: Okay? Then I was just like. I put. I can. I’m not going to share this with you today. Like, share the file, because I’m going to work through it with Jacob next week. But, like, point of sales, maybe you really only have point of sales for retail, though. You could say that you’re. You kind of have a point of sale for your E. Commerce. It’s just the same thing as your sales. Me: And then, yeah, maybe one thing to lie on too is like, you have point of sale for retail, but we actually, like, we sent a lot of product, so maybe there’s like some other team has, like, well, we sent this value a product, but this is the point of sale revenue that we’re getting. Them: Like you have. What you put in your dashboard was point of sales, right? Me: Yes. Yes. Them: And consumer buying at the register. Me: Yes. Them: Sales. Is what we’re selling to the retailer. Okay? Is that what you’re referring to with them? Okay? Me: Yeah. That’s what I’m referring to. Them: So that’s where I’m like, we’ve got point of sales, we got sales, we got revenue. Okay? Awaish. Go for it. Yeah, there’s one more thing here. Like for example, for Walmart, we also have part of sale data, but also Omni sales. Like, when the retail. We also get, like, the orders where it’s. It’s not sold in the store. But instead they. Maybe they ordered online and picked from the store or something like that. Me: One more piece. They ordered online, picked up in the store. But I think you’re right. Like, they’ll give you the finance version of this. You would have. Basically had, like, gross sales, and then you have, like, what you. What you net out. But then this is additionally we’re selling to the seller, so there’s even, like, one layer. Them: Yes. Me: Above that, you know? Them: Y. Eah, so. Sales definition. I think we’re all speaking the same language, which is good. Sales definition. What element sells to the wholesaler? What element sells to the retailers? What element sells to the end customers? What element sells? So drink element distribution with element sells to third party distribution. Okay, These are all our sources of sales. So then I was thinking, like, okay, if I wanted to go back to my geography question, just, like, as an example, Like, if I were to say, okay, well, I want to understand sales across all my channels in California or across my states or something. People are like, well, just because we sell to Target at large doesn’t mean that we know. The sales that are happening in California. So if I wanted to do some geo analysis, I’m realizing it’s not as simple as just saying, like, I want to see sales. It’s like. It’s like. And I don’t know if Omni will tell me this, right? If Omni will say no, if you want to understand things. Across geos. We’re going to pull in point of sales for retail. And then we’re going to pull in sales. For wholesale and E Commerce or whatever. Me: So this is where I would separate the second piece, which is like Will Omni. That is up to us. Like we can construct it to do so. So I think it’s more important for us to guide how we would like that type of complicated question to be answered. Them: Yeah. Me: Because ultimately, as you’re seeing, nobody. Is asking that question. Probably nobody understands all the nuance when they’re asking it. Whether. Whether they need to or not. But like we need to. Them: Right. And I didn’t until. I didn’t until today. That’s why I was kind of getting, like. I was picking out the, like, wholesale revenue, and wholesale revenue, I’m like. Me: Yes. Them: What? What does that mean? And also, so when I look at this, I’m like, okay, like, oh, this is starting to make sense to me. And it’s proving out that, like, maybe the question I’ve been hungry to ask from, like, this Omnichannel North Star view. Me: Yes, yes, yes. Yeah. Them: Is not as. Like if we were to say, I want to see contribution margin by channel. Eventually. There’s just, like, a delay on when you can see that, because it probably takes, like, closing out books. Like, I’m. I’m just like. We’ve been saying a lot of things in these Omni memories about what we can unlock, and I want to just be really realistic about it. Me: Yeah, yeah. Yeah. Cool. Yeah. So on the. On the. On the. On the Emerson side, we can show you. And, like, I think we. We do have a list of this, but it’s in the Emerson memo of, like, what are the things we have? So we do have geo level pos data. Them: And. Me: Also store level. So I do feel confident that that question, which is like, let’s canvas. I think a better maybe use a better question. There is actually. Them: Yeah. Me: Tell me about California and, like, where else in California we should go, right? Them: Yeah. Me: I think letting Omni actually look at what’s there to give you the story. And this is, again, just like how people are going to interact with it. Is better than saying, like, oh, I want to just combine these and get this. It’s more like, I’m interested in this topic. I’m interested in, like, looking at California or this region in California. I’m looking at, like. Tell me about what our POS data says. Telling you all the shipments that have been sent there. And how that’s trended. Tell me about all the ECOM orders that have been sent there. And, like, put the picture where in that sense. Them: I see. Me: You may not necessarily need to have the same ultimate definition in order to, like, arrive at. Them: The answer that you’re looking for. Me: You know, so that’s kind of framed. It’s more about, like, was the question. Like, the question was so direct, which restricts the way you answer versus Hey. Should we, like, put more. Should we, like, should we be selling more into the East Bay? Like, tell me about, like, what the East Bay has done for our business. Them: Would omni understand east bay. Me: Yeah, it will know what East Bay is. But again, more of the problem is, like, Ken doesn’t know the zip codes. Like, can it go from East Bay to here, the cities to then the zip codes? So then the. Yeah. Them: Yeah. So there’s a whole thing. You want to feed it around zip code stuff? Me: We are going to feed it as much context about element, whether it’s the way you guys talk about the business that isn’t in the data, like what skews or like what parts of the data matter a lot. In addition to just, like, the basic definitions of, like, the topic, which is, like, if you ask a question about sales, Here’s how you join Shopify to Amazon to answer that. That’s all on the topic. But there is this, like, there, there, there are these definitions about what element cares about or how element speaks about the data that you can’t look at the snowflake table and, like, infer that it’s just rows and columns. That’s actually the sauce. That we’re trying to add in the descriptions and the table descriptions, so this is actually really helpful. Like this is helpful for both the modeling, but actually we need to give AI all these caveats so that it can make the best recommendation. Them: Y. Me: Right. It can then say like, well, I do know that this is how wholesale looks at it. This looks at it. Them: Es. Me: What is this person asking me? And then ultimately, through our testing, we’ll find whether. It does that correctly, or it’s like, hey, your question. Actually, I don’t think you phrased your question properly. For a lot of our AI work, we’re finding that that is more of a thing, which is like the input question is not often precise enough. It’s like if you’re. We kind of described it as like. Think about it. You’re going, you’re an intern. You’re like, hey, give me all sales for, like, all these things. That’s, like, not fair to that intern. So part of this is the training where we have to train people to be a little bit more. Them: Yeah. Hand holding with their AI. Me: Yeah. Yeah. I mean, but. But, like. Because it. Yeah. So if you guys. I mean, you. Everybody uses chat GPT, so, you know, I do the same thing where I’m like, get me this. And I’m like, you totally, like, missed the ball, but I’m, like, didn’t say anything. Them: It’s totally true. Take me. Just to close this out. Me: Yeah. Them: Like we just talked about. Point of sales. We talked about sales. Revenue. Comes with its own baggage of like, what is net revenue, which is sales minus discounts minus refunds. In some of the systems, even though we don’t technically have. Like, we’re not discounting. But you see data show up under that discount column, right? Like in. In your wholesale table or whatever. Like the thing that Amber made for best review. So it’s like salesman’s discounts minus refunds, gross. Revenue would be sales minus discounts. Me: O. Kay. Them: And then net revenue sales minus discounts minus refunds. And then retail is the one that’s like chunky, like complicated. It’s like the sales minus the chargebacks, minus the trade spend money is the promotional events, minus the retail merchandising. And so, like, that one’s kind of meaty. So it was illuminating to me because if one day I want to say. Like what? Like I want Omni to be able to. I don’t know. I was just. I was like, if I want Omni to be able to tell me how, like, retail revenue has been. Like, is it just best for that to pull from QuickBooks and, like, tell me the number, or is it, like, it’s do all this math? Me: Yeah. Or maybe it should. Maybe it should say, like, I could do that in a couple ways. Like, tell me what’s best, or it answers it, but it explains. Like, here’s how I got to the answer. Them: Yeah. Either it’s like this is what they cited in QuickBooks. And one day, like, I know we’re not ingesting QuickBooks, but like, this is what was cited in our ERP. Or it’s like, I took sales, minus chargebacks, I don’t have anything for trade spend yet because I’m waiting on confido. Like, I’m. I’m just being a little bit, like, facetious here, but I’m like. I would want it to be really explicit if I’m wearing something with the AI like, where it’s feeling like it draws a blank versus it has information. Me: Yeah. Them: So that’s just the rundown. I’m going to sharpen this table up with Jacob next week. I’m going to be in person with him in Bozeman, and so, like, we’re going to, like, spend time on this table. Me: Okay? Them: But it’s just. Like a note for us when we say wholesale revenues. Just wholesale revenue. It’s like, no, that’s wholesale sales minus discounts, minus refunds. Me: Yeah. So if I can ask. If you can do. If you can try to, like, I can send you. Basically, what we talk about is, like, the profit equation, which is, like, from gross sales taxes, refunds, discounts. Returns. And then any variations of profit, like cost of goods and then cost of goods, shipping profit. If you could just, like, for these three channels, so you guys can just talk about those components. That’s perfect. So I can send you this equation. So for a lot of our clients, we drive towards, like, this, like, profit piece. Which is like net of all the different supply chain cogs, everything. And we may not have cogs, but we’re going to have shipping. We’re not discounts. Them: Yeah. Me: Refunds. Them: Yeah. So that’s a good call. So when I’m doing this exercise with Jacob, I just focused on, like, the commercial side of the business. But I can say, like, let’s say we made a different tab now with the same channels. But just how do you define cogs? Me: Yes. Them: How do you define whatever? Right? Like an open item that people keep saying, sorry, and we have I have to interview somebody out. But in open people item, people keep saying, it’s like, do we now have access to SKU level data for bundles? Like, people. That’s, like, a thing people have been wanting for a while, so it’s like people want to know, okay? Me: Yeah. So when you ask me about Amazon versus Shopify this morning, that is the nuance. Them: Yeah. Me: That, like, models the way we model Amazon for, like, other clients, we have to vary because you may want to bundle things. Some people are like, even if we sell a bundle, I want to see it all item level. Like I don’t care if it comes together. Them: Yeah. Me: That is the nuance about each like clients, Amazon or Shopify setup. Them: Totally. Me: Because you can. You can sell bundles, but then somebody like, I don’t care what package. If it comes together, I wanted to split it out. Them: Yeah. I need a hop, but this was good. Let’s try to ship that table to Phil by end of day. We can talk async if we need to, and then. And then we’ll just keep jamming on these, like, definitional things, okay? Me: Okay, okay. Okay? Sure. Yeah. And we’re sending updates on models and ingestion in the channel, but, yeah, I mean work. So I think if we’re fine with lasting, we’re fine with that omniplan, we’re going to take it out and start to run. Them: Yeah. Okay? Cool. Me: Okay? Okay? Them: Thank you. Me: Thank you, everybody. Them: Can you hang off for one more minute? Shivani, I don’t need you for this question. Yeah, yeah, I’m assigning you as host. Okay, bye. Okay, see you. Thanks. Hey, quick question. This question came out from our call with MHI and the nsuite integration. Me: Yes. Them: So right now, we’re. We’re pulling data from stored. Into Snowflake already, correct? Me: Cor. Rect. Yes, yes. Them: For the stored data. Are we also pulling in all the records tied to inventory movement? Or is it just the order data? That’s like being synced from Shopify. Do. Me: Do you know if this off your head? I’m going to go check the tables. Them: Specifically. Yeah. So, specifically, if there was an inventory movement from, like, one warehouse to another, Whether or not we’re tracking those, those transactions, because I believe those are created as requests in stored, but I didn’t know if that was some data that we were already pulling on. Me: So we’re getting. Them: So it says. Me: Yeah. Go ahead. Them: Like we do have inbounds and outbounds table. I don’t know if they can. Like inbound orders and outbound orders. Me: It looks like we have an inventory adjustments. Them: Okay? Me: Oh, we do have. So we have something called facility balances, which I think. Them: That might be. It’s. Me: Yeah. Yeah. Because it has facility available unit brand. Is it damaged? Them: In, okay? Me: Yeah, I can give you, like, a hundred line CSV of what’s in there. Them: If you don’t mind. Yeah, this came up because this is a new requirement that came out of the N integration. Jacobs asking that we pull the data for Snowflake that will provide, like. Me: Sure. Them: You know, some certain. Me: Ani just said she can’t. She can’t start her interview unless we mix this, so can I just send another zoom real quick? Them: All right. See ya. Yep. Me: Okay? Them: Bye.