Meeting Title: Brainforge Product Analytics Playbook Sync Date: 2025-09-04 Meeting participants: Shreya Chowdhury, Henry Zhao
WEBVTT
1 00:00:46.350 ⇒ 00:00:48.559 Henry Zhao: Hi there, how are you doing?
2 00:00:48.560 ⇒ 00:00:49.789 Shreya Chowdhury: Good, how are you?
3 00:00:50.170 ⇒ 00:00:50.730 Henry Zhao: Thanks.
4 00:00:52.460 ⇒ 00:00:53.320 Henry Zhao: Right.
5 00:00:54.450 ⇒ 00:00:56.970 Henry Zhao: How’s your… how long have you been at Brainforge?
6 00:00:57.300 ⇒ 00:01:02.909 Shreya Chowdhury: This is my second, or… I guess third week now?
7 00:01:03.280 ⇒ 00:01:04.809 Henry Zhao: Okay, how’s it going for you so far?
8 00:01:06.089 ⇒ 00:01:13.249 Shreya Chowdhury: Pretty good. Just been onboarding, sort of. I’ve been saying that for 2 weeks now, but I feel like every week there’s something that…
9 00:01:13.399 ⇒ 00:01:18.339 Shreya Chowdhury: knew that I haven’t set up yet, or need to learn about still.
10 00:01:18.469 ⇒ 00:01:19.379 Shreya Chowdhury: Yeah, I really…
11 00:01:19.380 ⇒ 00:01:25.479 Henry Zhao: We’ve been… I’ve been here two months, and I feel like I’m still onboarding also. But it’s very… it’s, like, very fast-paced. I really like it, actually.
12 00:01:25.670 ⇒ 00:01:35.240 Shreya Chowdhury: Yeah, no, it is super fast-paced. I feel like my first day, I started, and they just, like, threw some stuff at me for the client, and there was no, like,
13 00:01:35.870 ⇒ 00:01:39.290 Shreya Chowdhury: that was just like, here, like, this is what you gotta do. I was like, okay, cool.
14 00:01:39.560 ⇒ 00:01:41.670 Henry Zhao: Yeah, exactly. That’s exactly how it is.
15 00:01:43.300 ⇒ 00:01:46.210 Henry Zhao: Okay.
16 00:01:46.930 ⇒ 00:01:50.759 Henry Zhao: Let’s see… Where are you based out of?
17 00:01:51.260 ⇒ 00:01:53.770 Shreya Chowdhury: I’m in the Bay Area.
18 00:01:54.120 ⇒ 00:01:54.790 Henry Zhao: Okay.
19 00:01:54.790 ⇒ 00:01:56.379 Shreya Chowdhury: Yeah, what about you?
20 00:01:56.960 ⇒ 00:01:58.719 Henry Zhao: Nearby, in Arizona.
21 00:01:58.850 ⇒ 00:01:59.260 Shreya Chowdhury: Okay.
22 00:02:02.020 ⇒ 00:02:02.770 Henry Zhao: Cool.
23 00:02:04.170 ⇒ 00:02:08.300 Henry Zhao: Let’s see… so what did we want to talk about today? I already forgot that we’ve had so many meetings.
24 00:02:08.610 ⇒ 00:02:19.960 Shreya Chowdhury: Yeah, same. I was just trying to remember. I feel like there was a lot of things that we sort of got out of the way, like, there was default stuff that we talked about already, there…
25 00:02:19.960 ⇒ 00:02:21.170 Henry Zhao: Yesterday,
26 00:02:21.170 ⇒ 00:02:24.919 Shreya Chowdhury: Yeah, so I guess today we can kind of…
27 00:02:25.670 ⇒ 00:02:35.589 Shreya Chowdhury: We can walk through the product analytics playbook. I think I have some edits and stuff to make on the A-B testing side, and then.
28 00:02:35.590 ⇒ 00:02:36.140 Henry Zhao: That’s…
29 00:02:36.970 ⇒ 00:02:40.509 Shreya Chowdhury: I guess we can split up which ones we want to do?
30 00:02:40.620 ⇒ 00:02:42.650 Henry Zhao: Three that, Amber shared, right?
31 00:02:42.650 ⇒ 00:02:43.510 Shreya Chowdhury: Yeah.
32 00:02:45.530 ⇒ 00:02:54.489 Shreya Chowdhury: I think, yeah, we can do that first, and then get that out of the way, because I think Amber will need an answer for that, and then afterwards.
33 00:02:54.690 ⇒ 00:02:55.270 Henry Zhao: Sure.
34 00:02:56.400 ⇒ 00:03:07.959 Shreya Chowdhury: We can talk about other things. Like, if that’s the only thing that’s pressing for today, we can also just talk about that and set up another, like, 10 to 15 tomorrow to go over default stuff.
35 00:03:08.220 ⇒ 00:03:10.450 Henry Zhao: Sure. Yeah, whatever you want to do.
36 00:03:11.720 ⇒ 00:03:16.470 Shreya Chowdhury: Yeah, cool. So… So yeah, it looks like…
37 00:03:17.250 ⇒ 00:03:27.639 Shreya Chowdhury: The first three that they want to prioritize is cohort retention, funnel analysis, and feature adoption analysis.
38 00:03:33.350 ⇒ 00:03:34.940 Shreya Chowdhury: I can…
39 00:03:38.070 ⇒ 00:03:47.470 Shreya Chowdhury: I’m happy to take over… cohort retention… And…
40 00:03:53.080 ⇒ 00:04:16.399 Shreya Chowdhury: I guess I can do funnel analysis too, because I know Robert’s out this week. Are you down to take on feature adoption? And then also, for any of these cases, like, if you have other ideas for a sample case study, or something that would be cool, we can also add it. So if I do, like, the cohort retention one, and you come up with another interesting case, then we can have multiple, and that would be really cool.
41 00:04:17.170 ⇒ 00:04:22.559 Henry Zhao: Yeah, I’m gonna wait till you do one of yours, because I’m gonna kind of copy the format, just so that we’re, like, aligned in the…
42 00:04:22.560 ⇒ 00:04:22.910 Shreya Chowdhury: Yeah.
43 00:04:22.910 ⇒ 00:04:23.570 Henry Zhao: We’re…
44 00:04:23.570 ⇒ 00:04:32.089 Shreya Chowdhury: I think for the cohort retention one, that one’s probably gonna… like, I mean, the basic template is always really easy to do. That one is just kind of, like.
45 00:04:32.310 ⇒ 00:04:51.210 Shreya Chowdhury: creating, like, a dummy doc, like, what… explaining what cohort retention is, and I’ll usually just use AI to, like, come up with a good explanation. But as far as a case study goes, that’s where I think it’ll take a little bit more time, because for this one, like, I want to be more robust about generating, like, a synthetic dataset and, like.
46 00:04:51.210 ⇒ 00:04:57.940 Shreya Chowdhury: Going through and organizing it. So that one will probably take a little bit more time for this one,
47 00:04:58.510 ⇒ 00:05:05.550 Shreya Chowdhury: honestly, I want to say, like, with everything else, like, it’ll probably take me, like, at least a couple of days to do this one.
48 00:05:06.410 ⇒ 00:05:08.470 Shreya Chowdhury: Yeah, so what do you think?
49 00:05:09.700 ⇒ 00:05:11.980 Henry Zhao: Yeah.
50 00:05:12.470 ⇒ 00:05:18.930 Henry Zhao: I’ll wait to see this one, and then I’ll hold up on the case study, and I’ll just kind of copy your format
51 00:05:19.310 ⇒ 00:05:22.539 Henry Zhao: And maybe also use a little bit of AI to get this done.
52 00:05:22.540 ⇒ 00:05:26.150 Shreya Chowdhury: Okay, cool, yeah. And then…
53 00:05:26.950 ⇒ 00:05:32.470 Shreya Chowdhury: Okay, so do you want to wait until after I do the cohort one to start the feature adoption one? Or…
54 00:05:32.910 ⇒ 00:05:36.039 Henry Zhao: Yeah, just want to make sure we’re in the same, like, format.
55 00:05:36.590 ⇒ 00:05:49.099 Shreya Chowdhury: So, I can take on… I can start with the cohort retention template. Is there anything else we talked about in our meeting earlier today? I feel like there was a to-do or something that I may have forgotten to write down.
56 00:05:49.140 ⇒ 00:05:50.480 Henry Zhao: But I feel like…
57 00:05:52.940 ⇒ 00:05:54.010 Shreya Chowdhury: Is that what?
58 00:05:54.390 ⇒ 00:05:57.840 Henry Zhao: I think it was just this. Okay. Because we already talked about everything else, really.
59 00:05:57.840 ⇒ 00:05:59.950 Shreya Chowdhury: Okay, yeah. And then…
60 00:06:00.180 ⇒ 00:06:09.230 Shreya Chowdhury: for default stuff, I also feel like we may have had more to discuss, but then in the meeting yesterday, some of the stuff that we went over.
61 00:06:09.360 ⇒ 00:06:11.260 Henry Zhao: Yeah, we went over everything.
62 00:06:12.140 ⇒ 00:06:18.690 Shreya Chowdhury: Yeah, so for some of the default stuff, actually, maybe we can spend some time right now talking about it,
63 00:06:19.490 ⇒ 00:06:26.010 Shreya Chowdhury: I know yesterday we talked about all the data that we have, and how it’s, like, loaded, whatever,
64 00:06:27.070 ⇒ 00:06:29.280 Shreya Chowdhury: But,
65 00:06:31.690 ⇒ 00:06:40.849 Shreya Chowdhury: You said, do you want to go over some of the questions that they shared and that they want to get answered? I think that’s what we were going to do. We were gonna walk through the spreadsheet and see, like, who wants to take on what there.
66 00:06:42.460 ⇒ 00:06:46.669 Henry Zhao: Sure, so these are the questions. We can have, like, an owner, I guess.
67 00:06:52.000 ⇒ 00:07:04.630 Henry Zhao: Alright, so, hi Henry, thanks for the video walkthrough. I’m excited to have some actual visibility. I would like to get a light version of Product Analytics out ASAP, but important to know, most of these will not be relevant until new product is out, so I don’t want to waste time.
68 00:07:06.040 ⇒ 00:07:09.900 Henry Zhao: Alright, so we’re currently sales-led, that’s…
69 00:07:10.000 ⇒ 00:07:13.220 Henry Zhao: But that’s understandable, right? Moving to PLG and enterprise sales.
70 00:07:13.770 ⇒ 00:07:20.699 Henry Zhao: So what that means is right now they’re using Salesforce and Salespeople to bring in customers that are paid right now, so all customers are paid at the moment.
71 00:07:21.040 ⇒ 00:07:25.280 Henry Zhao: Soon they’re gonna have paid tiers and moving to a credit-based PLG.
72 00:07:25.790 ⇒ 00:07:29.679 Henry Zhao: And then back-end is changing to event-based architecture.
73 00:07:30.210 ⇒ 00:07:43.960 Henry Zhao: So we shouldn’t build out any of the analytics now that will need to be rebuilt in a month’s time. So, thinking lightweight, the areas that are going to be most valuable for build right now are… So, personas of who our customer base currently is. I think Utem is owning that right now.
74 00:07:44.070 ⇒ 00:07:47.010 Henry Zhao: Okay. What companies are using default? Same thing.
75 00:07:47.470 ⇒ 00:07:58.269 Henry Zhao: Are there trends in firmographics or usage? So we need to basically have some third-party data to say, like, these customers are in this industry, they’re this company size, they’re located here, they have this many sales reps, things like that.
76 00:07:59.070 ⇒ 00:07:59.830 Shreya Chowdhury: Okay.
77 00:08:00.800 ⇒ 00:08:03.379 Henry Zhao: Who are the users in default? I would say that’s the same thing.
78 00:08:08.280 ⇒ 00:08:14.990 Henry Zhao: And then out of these users, who are the power users? So, we need general usage for that, so we’re pending Vishal, adding…
79 00:08:15.910 ⇒ 00:08:17.940 Henry Zhao: User behavior data, okay?
80 00:08:17.940 ⇒ 00:08:18.680 Shreya Chowdhury: Okay.
81 00:08:20.800 ⇒ 00:08:22.629 Henry Zhao: That’s what he’s gonna be working on now.
82 00:08:23.000 ⇒ 00:08:26.340 Henry Zhao: Are there trends in power user person attributes?
83 00:08:27.160 ⇒ 00:08:30.679 Henry Zhao: so that’s the same thing as above, right?
84 00:08:34.280 ⇒ 00:08:40.330 Henry Zhao: Like, are power users more likely to be larger companies? Are they, like, mid-sized companies? Things like that, right?
85 00:08:40.600 ⇒ 00:08:43.779 Shreya Chowdhury: And then what actions are power users doing in the app?
86 00:08:43.780 ⇒ 00:08:45.979 Henry Zhao: So that’s, like, a mix of the ones above.
87 00:08:53.090 ⇒ 00:08:54.910 Henry Zhao: I mean, combo of above.
88 00:08:55.040 ⇒ 00:08:55.720 Henry Zhao: I guess.
89 00:08:56.750 ⇒ 00:09:00.160 Henry Zhao: Which users are receiving the most bookings in default?
90 00:09:00.360 ⇒ 00:09:02.060 Henry Zhao: So this is now available.
91 00:09:06.580 ⇒ 00:09:10.569 Henry Zhao: Meeting spot. This was just finished by Vishal.
92 00:09:10.720 ⇒ 00:09:12.160 Henry Zhao: So I can do this now.
93 00:09:14.120 ⇒ 00:09:16.789 Henry Zhao: Usage patterns for default users…
94 00:09:17.860 ⇒ 00:09:19.839 Henry Zhao: That’s the same as above, right?
95 00:09:22.720 ⇒ 00:09:26.550 Henry Zhao: We’ll just basically create, like, a waterfall chart in Amplitude, which is very easy.
96 00:09:27.220 ⇒ 00:09:28.000 Shreya Chowdhury: Okay.
97 00:09:28.000 ⇒ 00:09:31.939 Henry Zhao: How often do they visit? This is already available, so I can… I’m already working on that right now.
98 00:09:32.240 ⇒ 00:09:34.070 Henry Zhao: How much time do they spend?
99 00:09:34.560 ⇒ 00:09:38.630 Henry Zhao: That’s also… A mix of the above, right?
100 00:09:39.010 ⇒ 00:09:48.150 Henry Zhao: We need to know where they’re spending the time, but we’re almost there. We have, like, user data already. What are they doing? Same thing as above. A lot of this is, like, very repetitive.
101 00:09:49.070 ⇒ 00:09:51.160 Henry Zhao: Product usage patterns.
102 00:09:53.700 ⇒ 00:09:55.090 Henry Zhao: Yeah, it’s, like, very repetitive.
103 00:09:56.140 ⇒ 00:09:59.290 Henry Zhao: How many inbound leads are coming in daily or monthly?
104 00:09:59.480 ⇒ 00:10:02.689 Henry Zhao: That is now available, and you just need to look at…
105 00:10:06.980 ⇒ 00:10:08.820 Henry Zhao: Meetings booked.
106 00:10:09.470 ⇒ 00:10:11.690 Henry Zhao: And form submitted.
107 00:10:17.390 ⇒ 00:10:21.129 Henry Zhao: How many published workflows do we have? I think we have that now.
108 00:10:26.510 ⇒ 00:10:32.069 Henry Zhao: Average per customer, that’s available… just a calculation, right?
109 00:10:35.590 ⇒ 00:10:36.879 Henry Zhao: That’s very easy.
110 00:10:37.970 ⇒ 00:10:43.200 Henry Zhao: And then how many monthly demos are converting into opportunities? That’s already in Salesforce, so that’s available, and it’s in Salesforce.
111 00:10:43.500 ⇒ 00:10:44.250 Henry Zhao: Done.
112 00:10:44.570 ⇒ 00:10:52.830 Henry Zhao: What are the total number of default users versus active weekly default users? This is going to depend on, weighing definitions.
113 00:10:54.640 ⇒ 00:10:58.360 Henry Zhao: So… I can own this.
114 00:11:00.170 ⇒ 00:11:02.400 Henry Zhao: Will be defined next Wednesday.
115 00:11:02.950 ⇒ 00:11:03.960 Henry Zhao: September 10th.
116 00:11:06.530 ⇒ 00:11:13.720 Henry Zhao: Do you want to own the, like, the user behavior data stuff?
117 00:11:14.530 ⇒ 00:11:38.420 Shreya Chowdhury: Yeah, so, once the… I was thinking, once we have all that data available, if we could pull it in into, like, a CSV or something, like, I’ll let you set up the dashboard, because I know you’re already working on that end, like, for the monitoring, but I think it would be nice to provide the stakeholders with, like, a current state analysis on the user behavior, so we can just have, like, a brief write-up
118 00:11:38.420 ⇒ 00:11:44.690 Shreya Chowdhury: With, like, a complimentary slide deck, and just show, like, oh, we did, like, a deep dive into, like.
119 00:11:44.690 ⇒ 00:11:46.739 Shreya Chowdhury: The current state, like, this is what…
120 00:11:46.890 ⇒ 00:11:57.099 Shreya Chowdhury: These are the insights that we drew from the user behavior, and, like, we can drive some, like, product insights or, like, strategy, from that.
121 00:11:57.520 ⇒ 00:12:03.069 Henry Zhao: Maybe I can provide you the data, and then you can handle the insights and presentation piece of it, if you want.
122 00:12:03.070 ⇒ 00:12:10.260 Shreya Chowdhury: Yeah, great, that would be great, for this one, because I feel like I am onboarding a little bit late into the data, and you’re already, like, in the weeds of it.
123 00:12:10.260 ⇒ 00:12:13.610 Henry Zhao: It’s also not really efficient for us to both be working on kind of the same thing, like.
124 00:12:13.610 ⇒ 00:12:14.000 Shreya Chowdhury: Yeah.
125 00:12:14.220 ⇒ 00:12:15.419 Henry Zhao: brother’s heart.
126 00:12:15.420 ⇒ 00:12:16.090 Shreya Chowdhury: Yeah, okay.
127 00:12:16.090 ⇒ 00:12:23.180 Henry Zhao: We can also record you on it, so that you know, kind of, what I’m doing. Yeah. Like, if I’m out, or if you’re out, like, we kind of know what each other is doing.
128 00:12:23.180 ⇒ 00:12:37.840 Shreya Chowdhury: Yeah, cool, sounds good. Yeah, so, yeah, whenever you want to send over the data when that’s ready, I feel like for me, the work here for this particular, like, the product events and data stuff is, like,
129 00:12:38.460 ⇒ 00:12:40.110 Shreya Chowdhury: Yeah, just like the…
130 00:12:40.620 ⇒ 00:12:58.919 Shreya Chowdhury: the user insights, like, current state analysis, which is more of, like, a nice-to-have than anything. I think you pretty much have covered most of the bases here. This is, like, what we’re trying to get to for Ellie right now, so I’m in the… the pre-stages for this, with…
131 00:13:00.480 ⇒ 00:13:03.650 Shreya Chowdhury: Excuse me, with our other client,
132 00:13:04.090 ⇒ 00:13:16.189 Shreya Chowdhury: So we’re basically setting up, like, or we’re doing planning to set up, like, a lot of the tracking events, and then we’ll have that data, and eventually, hopefully, getting to this state with Ellie. But yeah, it seems like you guys are pretty far along here.
133 00:13:18.280 ⇒ 00:13:20.580 Henry Zhao: Cool, yeah, so I’ll let you know when we have the data.
134 00:13:20.930 ⇒ 00:13:24.500 Henry Zhao: At least the first round should be this week, so I’ll send you that when I have it.
135 00:13:24.500 ⇒ 00:13:33.629 Shreya Chowdhury: Okay, cool, sounds good. And then maybe, like, once I dig into that, we can probably use that for some of, our product analytics playbooks.
136 00:13:34.120 ⇒ 00:13:34.950 Henry Zhao: Yeah.
137 00:13:35.520 ⇒ 00:13:40.650 Shreya Chowdhury: Yeah. Okay, cool, sounds good. So then I’ll let…
138 00:13:40.960 ⇒ 00:13:46.589 Shreya Chowdhury: Amber know, like, that I’ll get started on…
139 00:13:47.830 ⇒ 00:13:56.710 Shreya Chowdhury: the template, the cohort analysis, if she wants to build out a ticket for that, and then…
140 00:13:56.850 ⇒ 00:14:00.479 Shreya Chowdhury: Are you fine to take on feature adoption analysis?
141 00:14:01.430 ⇒ 00:14:02.110 Shreya Chowdhury: Mmm…
142 00:14:02.110 ⇒ 00:14:04.040 Henry Zhao: If you want to take it, it’s fine also.
143 00:14:05.530 ⇒ 00:14:16.550 Shreya Chowdhury: Oh, well, I think they said, like, Utam and Amber were saying that they want to split it. I’m fine to take it on, I just will go one at a time, so I’ll probably do cohort retention first, and then I’ll do the other one.
144 00:14:16.550 ⇒ 00:14:22.130 Henry Zhao: Yeah, then I’ll copy yours for featured adoption while you do bono analysis.
145 00:14:22.380 ⇒ 00:14:26.819 Shreya Chowdhury: Okay, cool. Yeah, we can let them know the plan.
146 00:14:27.320 ⇒ 00:14:31.099 Shreya Chowdhury: Yeah, alright, I think that sounds good. Yeah.
147 00:14:33.100 ⇒ 00:14:35.140 Shreya Chowdhury: Yeah, that’s pretty much everything I had.
148 00:14:36.570 ⇒ 00:14:43.640 Henry Zhao: Cool, so then I will… I’ll wait for you.
149 00:14:44.540 ⇒ 00:14:47.550 Henry Zhao: And then… we’ll continue to keep in touch, I guess.
150 00:14:47.550 ⇒ 00:14:49.590 Shreya Chowdhury: Alright, cool, sounds good. Bye, take care.
151 00:14:50.050 ⇒ 00:14:50.589 Henry Zhao: Take care.