Meeting Title: Mother Duck Forecasting Sync Date: 2026-01-28 Meeting participants: Pranav Narahari, Bobby Palmieri
WEBVTT
1 00:00:47.840 ⇒ 00:00:48.710 Bobby Palmieri: Hello, sir.
2 00:00:51.810 ⇒ 00:00:53.039 Pranav Narahari: Hello, hello!
3 00:00:53.400 ⇒ 00:00:54.220 Bobby Palmieri: How are ya?
4 00:00:54.610 ⇒ 00:00:56.130 Pranav Narahari: Pretty good, pretty good.
5 00:00:58.340 ⇒ 00:01:04.410 Pranav Narahari: Just had a call with Mother Duck, yeah, so…
6 00:01:05.050 ⇒ 00:01:22.639 Pranav Narahari: basically, just kind of, like, 60-second, like, update on that is, there’s currently a PR out right now that Sam just, actually saw that there’s some movement on. There wasn’t some movement for a few weeks, but, today there was some movement on it, and hoping they can…
7 00:01:22.960 ⇒ 00:01:40.599 Pranav Narahari: it’s essentially a patch for the issue that we’re having right now. And so, if they push that in, like, in the next couple days, we’ll continue using MotherDuck. If not, AirByte has a ton of other, like, data warehouse connectors, and there’s ones that they suggest even over Mother Duck.
8 00:01:40.600 ⇒ 00:01:47.260 Pranav Narahari: So, like Snowflake. And so, there’s some other ones too, like S3, as well, so…
9 00:01:48.000 ⇒ 00:01:52.600 Pranav Narahari: Like, there’s a range of, like, in terms of, like, pricing, like, options, as well as just, like…
10 00:01:52.760 ⇒ 00:02:06.000 Pranav Narahari: In general, just, like, a whole catalog of different data warehouse options, so… either way, we’re not, like… we’re not worried, we’re just trying to see, like, what is the best option, since we kind of chose Mother Duck, maybe…
11 00:02:06.250 ⇒ 00:02:14.399 Pranav Narahari: If they can patch this, that would be great, and we also have a partnership with them, so, we feel like we can get the support there, but either way, we’re not too worried.
12 00:02:14.680 ⇒ 00:02:15.200 Bobby Palmieri: Boom.
13 00:02:15.500 ⇒ 00:02:27.179 Pranav Narahari: Yeah, just a quick update on that. But yeah, I wanted to talk a little bit about the… the forecaster. Maybe we can just, like, hop into your lit real quick.
14 00:02:28.310 ⇒ 00:02:31.620 Pranav Narahari: And… I’ll just share my screen.
15 00:02:42.720 ⇒ 00:02:44.680 Pranav Narahari: Okay. So…
16 00:02:45.100 ⇒ 00:02:51.220 Pranav Narahari: On this view, this is, like, the main view that I see that, you know, the Shopify data.
17 00:02:51.390 ⇒ 00:02:51.720 Bobby Palmieri: Nope.
18 00:02:51.720 ⇒ 00:03:01.909 Pranav Narahari: is… is populating, right? Like, Meta, Google here, like, this is more just, centric to… Those specific connections.
19 00:03:01.910 ⇒ 00:03:03.110 Bobby Palmieri: Yes, correct.
20 00:03:03.110 ⇒ 00:03:04.960 Pranav Narahari: And then, same with Klaviyo, right?
21 00:03:04.960 ⇒ 00:03:06.320 Bobby Palmieri: Correct, yep.
22 00:03:06.320 ⇒ 00:03:09.749 Pranav Narahari: And so this revenue data, that comes in from Klaviyo as well.
23 00:03:10.000 ⇒ 00:03:10.800 Bobby Palmieri: Yes.
24 00:03:10.930 ⇒ 00:03:15.499 Pranav Narahari: Perfect. Okay, so then let’s just focus here on all channels.
25 00:03:16.360 ⇒ 00:03:30.170 Pranav Narahari: So, I think my questions are more from, like, a UI perspective. I feel like I understand, like, where all this data comes from, how it’s being calculated, etc, like, based on, like, that… that recording you sent a while back.
26 00:03:30.480 ⇒ 00:03:36.000 Pranav Narahari: So, with that Python script, what…
27 00:03:36.300 ⇒ 00:03:44.359 Pranav Narahari: what exactly was that Python script doing? I was under the assumption that it was, like, taking in all the Shopify, like, data, and then…
28 00:03:44.460 ⇒ 00:03:49.230 Bobby Palmieri: Extracting, like, what’s new customer revenue versus existing customer revenue, etc.
29 00:03:49.420 ⇒ 00:03:54.910 Bobby Palmieri: No, so that… so if you go to monthly forecast, Yeah. On the left-hand side.
30 00:03:56.150 ⇒ 00:03:59.150 Bobby Palmieri: And then just, like, view a scenario.
31 00:04:01.780 ⇒ 00:04:14.340 Bobby Palmieri: Essentially, like, what that was supposed to do was forecast out the returning customers, so it would say, like, hey, over the last 3 years, by month, here’s how many new customers
32 00:04:14.560 ⇒ 00:04:15.950 Bobby Palmieri: you’ve acquired?
33 00:04:16.269 ⇒ 00:04:17.209 Pranav Narahari: Gotcha.
34 00:04:17.209 ⇒ 00:04:25.649 Bobby Palmieri: And then, like, based on that, you know, here’s how many we expect to return in January, February, March, April, May.
35 00:04:25.829 ⇒ 00:04:27.179 Bobby Palmieri: etc.
36 00:04:28.720 ⇒ 00:04:31.020 Pranav Narahari: Oh, okay. Gotcha.
37 00:04:31.250 ⇒ 00:04:32.170 Bobby Palmieri: So…
38 00:04:32.800 ⇒ 00:04:36.920 Pranav Narahari: Yeah, that part is no longer needed for, like, this phase.
39 00:04:36.920 ⇒ 00:04:45.919 Bobby Palmieri: For this phase, correct. So if you go back to the daily forecasting, All we need is,
40 00:04:46.100 ⇒ 00:04:54.940 Bobby Palmieri: you know, ad spend is just Meta plus Google spend, new customer revenue, you know, existing customer revenue, etc.
41 00:04:55.140 ⇒ 00:04:56.430 Bobby Palmieri: In that regard.
42 00:04:57.010 ⇒ 00:05:04.370 Pranav Narahari: Okay, gotcha. And so… Alright, so in terms of, like, the monthly forecasting page.
43 00:05:04.370 ⇒ 00:05:06.450 Bobby Palmieri: We don’t need this for V1.
44 00:05:06.650 ⇒ 00:05:10.960 Pranav Narahari: Gotcha, okay, I was just about to say that. So, the only thing that, like…
45 00:05:10.960 ⇒ 00:05:16.190 Bobby Palmieri: We’re gonna bypass that, and just, in the daily tab.
46 00:05:16.590 ⇒ 00:05:20.080 Bobby Palmieri: You’re just gonna be able to edit those goals for the month.
47 00:05:21.510 ⇒ 00:05:23.170 Pranav Narahari: These monthly snapshot goals.
48 00:05:23.170 ⇒ 00:05:23.920 Bobby Palmieri: Yes.
49 00:05:23.920 ⇒ 00:05:40.939 Pranav Narahari: Yeah, okay, perfect. And then, in terms of, like, when we say, like, compare up here, like, forecast last month, last year, so, I’m guessing last year, like, it shouldn’t just show one month. I know this is just, like, a demo, so that’s why it shows a month, but it should have, like, 365 rows here.
50 00:05:41.210 ⇒ 00:05:46.540 Bobby Palmieri: No, it should be, like, January of 2024, or 2025.
51 00:05:46.540 ⇒ 00:05:48.740 Pranav Narahari: Okay, so year-to-date, gotcha.
52 00:05:48.740 ⇒ 00:05:52.229 Bobby Palmieri: Well, I think this is a monthly snapshot, right?
53 00:05:54.480 ⇒ 00:05:58.880 Pranav Narahari: So when we click on compare to last year, what are we… what are we.
54 00:05:58.880 ⇒ 00:06:00.780 Bobby Palmieri: January over January.
55 00:06:00.780 ⇒ 00:06:05.809 Pranav Narahari: Gotcha, gotcha. Okay, so it’s always a monthly snapshot, okay, that makes sense to me.
56 00:06:07.370 ⇒ 00:06:08.480 Pranav Narahari: Okay, perfect.
57 00:06:08.480 ⇒ 00:06:15.279 Bobby Palmieri: And the other thing that I would say, like, last year, last month, I don’t… like, I assume once everything’s set up, this is
58 00:06:15.420 ⇒ 00:06:23.080 Bobby Palmieri: fairly easy to do it. First forecast, first last year, versus last month, but forecast is the most important for the time being.
59 00:06:23.250 ⇒ 00:06:35.769 Pranav Narahari: Okay, perfect. Yeah, I think for this POC, let’s just… we’ll just, like you said, yeah, it’s really just a UI and, like, pulling the data from the data warehouse to kind of get…
60 00:06:35.900 ⇒ 00:06:46.619 Pranav Narahari: more comparisons out there for last year, last month, whatever. So, not too concerned about pushing those out after. So yeah, focusing on forecast… sounds good.
61 00:06:46.940 ⇒ 00:06:58.500 Pranav Narahari: Yeah, I would still say, like, we’re on track for that, for sure. I know that there’s been a little bit of a hiccup with AirByte, but we have so many options there, so…
62 00:06:58.500 ⇒ 00:07:00.619 Bobby Palmieri: The new customer thing?
63 00:07:01.270 ⇒ 00:07:06.220 Pranav Narahari: So that’s the thing with AirByte right now, that’s the blocker for that.
64 00:07:07.030 ⇒ 00:07:10.450 Pranav Narahari: We’re not able to pull in the…
65 00:07:10.900 ⇒ 00:07:18.430 Pranav Narahari: it’s the orders data is having some issues being pulled in from AirByte, or through AirByte into Mother Duck.
66 00:07:18.770 ⇒ 00:07:19.880 Pranav Narahari: And…
67 00:07:20.070 ⇒ 00:07:26.310 Pranav Narahari: I know how we would go about doing it. I’ve basically have, like, a SQL query, like, written up.
68 00:07:26.450 ⇒ 00:07:41.899 Pranav Narahari: in… that I’ve been trying to do in Mother… in Mother Duck. However, we just don’t have the data coming in yet, so I can’t test it against the data that’s in the Shopify dashboard. Like, all the data looks off, but that’s to be expected.
69 00:07:42.200 ⇒ 00:07:43.810 Bobby Palmieri: Okay. Yeah. Cool.
70 00:07:43.810 ⇒ 00:07:46.619 Pranav Narahari: I would still say, yeah, we’re still tracking well there,
71 00:07:46.740 ⇒ 00:07:50.000 Pranav Narahari: that’s why I’m pushing our team a little bit to…
72 00:07:50.130 ⇒ 00:07:55.560 Pranav Narahari: get this done sooner than later. I know in our Gantt chart, we have until, like.
73 00:07:55.580 ⇒ 00:08:11.060 Pranav Narahari: next week to still be, like, on track for setting up the data warehouse, but since we have, like, some of these dependencies, like, we still want to make sure we’re pulling in the right new customer revenue, and, like, we have the right queries in place, or whatever, to make sure we’re, like.
74 00:08:11.320 ⇒ 00:08:17.569 Pranav Narahari: having the right… like, no data discrepancies there. I’m just trying to push us to get that done, like, this week.
75 00:08:17.700 ⇒ 00:08:18.460 Pranav Narahari: Awesome. So…
76 00:08:18.460 ⇒ 00:08:19.459 Bobby Palmieri: I appreciate it.
77 00:08:19.460 ⇒ 00:08:30.410 Pranav Narahari: Yeah, totally. Yeah, in terms of just, like, timeline overall, I… I think we haven’t talked about that too much. Maybe you and Utam have talked about it.
78 00:08:30.550 ⇒ 00:08:38.050 Pranav Narahari: But… Yeah, like, next week, and I think I mentioned this in the last call, maybe not,
79 00:08:38.179 ⇒ 00:08:57.399 Pranav Narahari: we want to have a POC out for you guys by next Friday. And so, when I say we’re tracking well, like, that’s what I’m using as, like, the milestone that we’re gonna hit. And that includes, like, the end-to-end flow from Shopify through whatever ETL tool we’re using, whether it be AirByte or something else.
80 00:08:57.480 ⇒ 00:09:03.149 Pranav Narahari: into Mother Duck, into the Stitch platform. And so, we’ll have that specifically for…
81 00:09:03.410 ⇒ 00:09:09.499 Pranav Narahari: Shopify, and then we’ll also have this forecasting dashboard populate with that data from Shopify.
82 00:09:10.130 ⇒ 00:09:10.790 Bobby Palmieri: Awesome.
83 00:09:10.790 ⇒ 00:09:11.570 Pranav Narahari: Yeah.
84 00:09:13.170 ⇒ 00:09:16.969 Pranav Narahari: Cool. That was, that was all I had.
85 00:09:16.970 ⇒ 00:09:32.049 Bobby Palmieri: Yeah, I think good on my end. I’m gonna send some notes in the channel, like, our, EA is back, so I want to get you guys all of the API keys tomorrow so that we can load those.
86 00:09:32.240 ⇒ 00:09:33.789 Bobby Palmieri: And then go from there.
87 00:09:34.170 ⇒ 00:09:43.920 Pranav Narahari: Perfect, yeah, that should be quick. Once we get that, like, that, you know, whatever data sheet, like, Sam should have no problem just, like, throwing that to the API, and then just getting everything populated.
88 00:09:44.200 ⇒ 00:09:45.769 Bobby Palmieri: Awesome. Sounds great to me.
89 00:09:46.060 ⇒ 00:09:47.440 Pranav Narahari: Cool. Thanks, Bobby.
90 00:09:47.440 ⇒ 00:09:48.280 Bobby Palmieri: Thank you.
91 00:09:48.580 ⇒ 00:09:49.639 Pranav Narahari: Have a good one. See ya.
92 00:09:49.640 ⇒ 00:09:50.250 Bobby Palmieri: Later.