Meeting Title: Global VetLink Analytics Strategy Discussion Date: 2026-02-09 Meeting participants: Robert Tseng, Kat Gillis
WEBVTT
1 00:08:04.430 ⇒ 00:08:05.360 Kat Gillis: Hi!
2 00:08:05.580 ⇒ 00:08:06.290 Robert Tseng: Hi, Cat.
3 00:08:07.040 ⇒ 00:08:10.529 Kat Gillis: So sorry about that, I could not stop the call.
4 00:08:10.530 ⇒ 00:08:15.029 Robert Tseng: No worries. I mean, that was… that was real fast. I was, like, trying to draft an email saying, it’s okay, take your time, and then…
5 00:08:15.930 ⇒ 00:08:16.660 Robert Tseng: That you set up, so…
6 00:08:16.660 ⇒ 00:08:19.340 Kat Gillis: How are you doing?
7 00:08:19.640 ⇒ 00:08:25.109 Robert Tseng: I’m doing well. I’m at an airport right now, so apologies if there’s background noise, but
8 00:08:25.550 ⇒ 00:08:30.199 Robert Tseng: Yeah, just, coming, coming back. I’m flying back to New York in a few hours.
9 00:08:30.640 ⇒ 00:08:33.960 Kat Gillis: Nice. Are you based in New York City?
10 00:08:34.250 ⇒ 00:08:38.210 Robert Tseng: Yeah, I’m in… I’m in Manhattan. Yeah.
11 00:08:38.710 ⇒ 00:08:47.000 Kat Gillis: Great. We, my husband and I lived there for 4 years, now we’re in Boise, Idaho, so we left the big city life behind, but…
12 00:08:47.000 ⇒ 00:08:47.660 Robert Tseng: Oh.
13 00:08:48.880 ⇒ 00:08:55.860 Robert Tseng: Yeah, I mean, I’m curious, did you meet your husband there, or did you meet him before and moved there, and then just wanted to do a short.
14 00:08:55.860 ⇒ 00:09:07.909 Kat Gillis: Yeah, we met in college, then moved to the city. I took a job, he went to law school, and we knew post-law school that we did not want to stay.
15 00:09:08.270 ⇒ 00:09:15.810 Kat Gillis: So, yeah, we moved first to Seattle, and then we were like, Seattle’s also too big, and then moved to Idaho.
16 00:09:16.200 ⇒ 00:09:18.890 Robert Tseng: Wow, that’s… that’s awesome.
17 00:09:18.890 ⇒ 00:09:19.600 Kat Gillis: So we were…
18 00:09:19.600 ⇒ 00:09:24.540 Robert Tseng: are in a similar mindset. We will probably not be in New York long-term.
19 00:09:24.540 ⇒ 00:09:29.980 Kat Gillis: Yeah, yeah. I mean, we have 4 little kids, pregnant with our 5th, so there was.
20 00:09:29.980 ⇒ 00:09:30.660 Robert Tseng: Wow.
21 00:09:30.660 ⇒ 00:09:34.610 Kat Gillis: that we were doing the city life with, yeah, our children.
22 00:09:34.610 ⇒ 00:09:35.260 Robert Tseng: Yeah.
23 00:09:35.260 ⇒ 00:09:41.989 Kat Gillis: Well, congrats, I mean, that’s super special to be building a family. Yeah, thank you. Yeah.
24 00:09:42.390 ⇒ 00:09:46.599 Kat Gillis: Okay, cool. Well, we can chat about whatever would be useful for you.
25 00:09:46.860 ⇒ 00:09:51.020 Robert Tseng: Sure, yeah, I mean, I took around… I clicked around Global VetLink, is that correct?
26 00:09:51.200 ⇒ 00:09:51.790 Kat Gillis: Yeah.
27 00:09:51.940 ⇒ 00:10:09.629 Robert Tseng: Okay, yeah, I mean, I was, my understanding, maybe… let me just level set on that as, like, compliance software, and I actually thought it was really cool that you had, like, the… kind of, like, a little module where you could test out the platform, and then you have all the coach marks that kind of walk you through the platform in there. I don’t see that very often in product.
28 00:10:09.630 ⇒ 00:10:10.030 Kat Gillis: I don’t know.
29 00:10:10.030 ⇒ 00:10:27.450 Robert Tseng: I wonder how much that gets used, and yeah, I mean, that’s a really… it’s… because normally people gate it so that you have to, like, sign in, and sign up, and then go through all of that, but yeah, I mean, I thought… I’m curious. I mean, that’s a really nitpicky thing, but, like, I wonder how that… how that’s.
30 00:10:27.750 ⇒ 00:10:28.170 Kat Gillis: Yeah.
31 00:10:28.170 ⇒ 00:10:28.679 Robert Tseng: How much attraction.
32 00:10:28.680 ⇒ 00:10:40.319 Kat Gillis: It’s through a platform called, Nevadic, N-A-V-A-T-T-I-C, and our marketing team just built out, basically, a demo
33 00:10:40.460 ⇒ 00:10:50.269 Kat Gillis: flow, so it’s not our actual product. Yeah. And… yeah, we get, like, 1,500 visitors a month, which is decent for us.
34 00:10:50.720 ⇒ 00:10:51.620 Kat Gillis: Yeah.
35 00:10:51.620 ⇒ 00:10:53.850 Robert Tseng: Just through that alone, or in total?
36 00:10:53.850 ⇒ 00:10:55.820 Kat Gillis: Just through that alone.
37 00:10:55.820 ⇒ 00:10:56.450 Robert Tseng: Okay.
38 00:10:56.780 ⇒ 00:11:03.389 Kat Gillis: So more than that, we get higher traffic to the website, but then 1,500 people from the website click through the demo.
39 00:11:03.820 ⇒ 00:11:15.979 Robert Tseng: Yeah, and I guess kind of on that note, in terms of how you’re driving traffic to your website, I’m kind of curious, like, what… is it mostly paid ads, or kind of what’s… what’s, how are you… how are you doing top of funnel awareness?
40 00:11:15.980 ⇒ 00:11:24.049 Kat Gillis: Yeah, so, I mean, one, you’ll notice the website is terrible, so I’m… I just joined the business, first thing is that we’re redoing the website, redoing…
41 00:11:24.050 ⇒ 00:11:45.220 Kat Gillis: the sign-up CTAs and the sign-up form itself, like, it’s all bad. but predominantly, yeah, we do paid ads. Most of our traffic is organic. We have 70% market share, people… we’re the market leader, people know the name. A lot of people are just Googling directly, Global VetLink,
42 00:11:45.480 ⇒ 00:11:54.260 Kat Gillis: they find us through vet clinics that are already pregnant, so… Yeah, it’s been… It…
43 00:11:54.420 ⇒ 00:12:00.359 Kat Gillis: it’s been an interesting… I haven’t been in this type of a business before, where they just, like, everyone knows you, and…
44 00:12:00.360 ⇒ 00:12:00.960 Robert Tseng: Yeah.
45 00:12:01.010 ⇒ 00:12:04.420 Kat Gillis: Sometimes throwing dollars at the problem doesn’t even really help.
46 00:12:04.880 ⇒ 00:12:09.440 Robert Tseng: Yeah. No, I mean, it’s great. I mean, seems like it’s a pretty strong, yeah, niche. I mean, I…
47 00:12:09.440 ⇒ 00:12:09.790 Kat Gillis: Yeah.
48 00:12:09.790 ⇒ 00:12:11.220 Robert Tseng: I checked, just like…
49 00:12:11.350 ⇒ 00:12:21.250 Robert Tseng: just using ChatGPT, Badras, trying to see, like, if the AI search results would pull you, and you’re the top for everything, so, like, I figured it’s been around for a while.
50 00:12:21.250 ⇒ 00:12:29.639 Kat Gillis: Yes, yeah. I’ll go ahead and share… so, I oversee our product and marketing teams, and that’s kind of where
51 00:12:29.750 ⇒ 00:12:39.210 Kat Gillis: the intersection of Pendo is happening, so… I’m having two issues with Pendo. The first is that…
52 00:12:39.360 ⇒ 00:12:45.669 Kat Gillis: Someone on the product team who’s not there anymore went in and set up a bunch of events.
53 00:12:45.820 ⇒ 00:12:59.310 Kat Gillis: I don’t know if these are good or bad, there’s 68 of them, it’s a mishmash of naming. My current product team also, you know, I think someone just needs to force them to sit down and define, like.
54 00:12:59.930 ⇒ 00:13:10.670 Kat Gillis: this is the core stuff that we want to look at, and then ideally, I could go to a dashboard and see how that stuff is growing over time. Nobody knows how to add new events, which…
55 00:13:10.670 ⇒ 00:13:29.109 Kat Gillis: I know we could just do, like, a Pendo course, but… yeah. Yeah. And then the other side is that because it is a predominantly self-serve, 75% of our revenue comes from people just signing up themselves, so I think that we should be making much more use of
56 00:13:29.600 ⇒ 00:13:35.830 Kat Gillis: emails, notifications, whatever, when people don’t complete certain actions, which…
57 00:13:35.830 ⇒ 00:13:36.480 Robert Tseng: Totally.
58 00:13:36.830 ⇒ 00:13:38.970 Kat Gillis: I think happens through events in Pendo?
59 00:13:39.540 ⇒ 00:13:43.519 Kat Gillis: Like, if… if they sign up, but haven’t…
60 00:13:43.910 ⇒ 00:13:49.890 Kat Gillis: put in their credit card information or something, then we could notify them.
61 00:13:50.210 ⇒ 00:13:52.179 Kat Gillis: But I’m not sure if Pendo can do that.
62 00:13:52.800 ⇒ 00:13:56.120 Robert Tseng: Yeah, a little bit of a gray area in terms of, like.
63 00:13:56.280 ⇒ 00:14:02.310 Robert Tseng: I don’t think, natively, it will capture the drop-off accurately. Okay. It depends on, like.
64 00:14:02.330 ⇒ 00:14:19.730 Robert Tseng: what your, sign-up or intake form kind of provider is, and if there’s a direct integration with Pendo. But if it’s your native site, and they’re all native intakes, should be no problem. But obviously certain third providers… third-party providers would probably be a bit difficult to work with, but…
65 00:14:19.730 ⇒ 00:14:28.979 Robert Tseng: you can work around that. And then second, like, the follow-up message is probably not through Pendo either, it’s probably through your customer engagement platform. I don’t know if you use, like.
66 00:14:28.980 ⇒ 00:14:29.710 Kat Gillis: But, yeah.
67 00:14:29.710 ⇒ 00:14:34.779 Robert Tseng: I see HubSpot here, so I imagine you’re probably a HubSpot company, yeah.
68 00:14:35.760 ⇒ 00:14:37.160 Kat Gillis: Yeah,
69 00:14:37.550 ⇒ 00:14:55.119 Kat Gillis: Okay, that makes sense. I mean, right now, what is happening is we’ve defined 3 critical drop-off points, which is if someone signed up and hasn’t actually created their first certificate. So what is happening is every other day, an engineer downloads a list of emails of those users.
70 00:14:55.300 ⇒ 00:15:09.470 Kat Gillis: emails them to the marketing team, and then the marketing team loads them into HubSpot and sends an email, and I was like, there’s no way in 2026 that we can’t automate this. So, yeah, little things like that.
71 00:15:09.790 ⇒ 00:15:10.370 Robert Tseng: Okay.
72 00:15:10.510 ⇒ 00:15:11.250 Robert Tseng: Yeah.
73 00:15:13.800 ⇒ 00:15:18.430 Kat Gillis: Okay, that’s kind of the lay of the land.
74 00:15:18.820 ⇒ 00:15:19.349 Kat Gillis: In and out.
75 00:15:19.350 ⇒ 00:15:19.970 Robert Tseng: Okay.
76 00:15:20.270 ⇒ 00:15:44.729 Robert Tseng: Yeah, I mean, I have a few more questions, just based on what you showed me. So, I saw you had about 70 tracked events, I already saw a bunch of duplicates, and just, like, I mean, yeah, just as far as naming conventions. I guess, kind of before I get into, like, kind of the instrumentation nitty-gritty, I want to step back a bit. You said Pendo was kind of set up before. How actively is it being used currently? Like, I just want to get a sense of, like, how sticky is this platform for your organization? Are you… do you feel like you have to stay on Pendo?
77 00:15:44.730 ⇒ 00:15:45.470 Robert Tseng: I… yeah.
78 00:15:45.630 ⇒ 00:15:49.989 Kat Gillis: Yeah, The marketing team uses it
79 00:15:50.510 ⇒ 00:16:04.269 Kat Gillis: daily for guides, and, like, feature notification pop-ups and webinar promos. They could easily learn to do that in another tool. It doesn’t need to be Pendo. Okay.
80 00:16:04.410 ⇒ 00:16:10.250 Kat Gillis: It is installed now, and… You know, but yeah, I used…
81 00:16:10.830 ⇒ 00:16:13.160 Kat Gillis: I forget what I used at a prior company.
82 00:16:13.160 ⇒ 00:16:18.240 Robert Tseng: Yeah, I was gonna… that was my next question. What’s your experience with product analytics tools, and what have you used? Yeah.
83 00:16:18.240 ⇒ 00:16:20.480 Kat Gillis: What is one of Pendo’s competitors?
84 00:16:20.480 ⇒ 00:16:26.840 Robert Tseng: Amplitude, MixedPanel, Post AUG, because, yeah.
85 00:16:26.840 ⇒ 00:16:30.610 Kat Gillis: I’ve used Amplitude, but does Amplitude do in-app guides?
86 00:16:31.140 ⇒ 00:16:32.489 Robert Tseng: It does now, yeah.
87 00:16:32.670 ⇒ 00:16:39.499 Kat Gillis: Okay. I want to say we were using amplitude for analytics, segment plus amplitude. Yep.
88 00:16:39.890 ⇒ 00:16:51.080 Kat Gillis: But we may have been using Pendo for guides, because Amplitude didn’t have a guide yet. So, anyway, I… I have not… I’m not super familiar with any tool, so I am fairly tool agnostic. Okay.
89 00:16:52.230 ⇒ 00:16:55.429 Robert Tseng: So it doesn’t need to be Pendo, but the team is…
90 00:16:55.430 ⇒ 00:16:57.609 Kat Gillis: The marketing team is actively using it.
91 00:16:57.920 ⇒ 00:17:08.020 Robert Tseng: Yeah, I mean, what I’ll say with this is just, like, it makes sense to me. If it’s a marketing, non-technical team, that’s primarily using it for in-app guides, like, I understand why your team went with Pendo.
92 00:17:08.270 ⇒ 00:17:18.930 Robert Tseng: I think where it gets tricky, which maybe is what you’re seeing now, is Pendo is really good at helping people to create events off of just the UI alone, so it’s like a very much, like.
93 00:17:19.359 ⇒ 00:17:38.699 Robert Tseng: click-based kind of UI tool where you can easily build, events, but it’s hard to govern, because then you have too many people, like, kind of, too many cooks in the kitchen, right? And so, governance tends to be kind of crazy, there isn’t, like, a strict tracking plan that it follows, and so you basically need, like, other processes outside of Pendo to really standardize, the tracking plan.
94 00:17:38.889 ⇒ 00:17:52.509 Robert Tseng: Which is totally fine. I think every tool has its challenges, and frankly, when I work with a client, like, on starting and doing this, well, how I typically work is, first, I’ll do, like, an event data design exercise, so…
95 00:17:52.739 ⇒ 00:18:07.649 Robert Tseng: I guess I could… I could send you some… some things to look at after this call in your own time, but, how it works is, yeah, take a look at your existing events. Look, we consolidate workflows to try to focus on… so, yeah, it’ll… typically what you… what we find is, like.
96 00:18:07.779 ⇒ 00:18:21.789 Robert Tseng: most companies we work with can get by with, like, 20 or fewer events, tracked events. It’s a lot easier, to, to, to keep track of, and then, like, scale… as far as, like, scalability, it’s easier to manage.
97 00:18:21.889 ⇒ 00:18:24.209 Robert Tseng: And then, I think…
98 00:18:24.609 ⇒ 00:18:32.319 Robert Tseng: really building out the core funnel reports so you can find the drop-offs. Sounds like you already have an intuition for where those drop-offs are, which is great. That makes…
99 00:18:32.379 ⇒ 00:18:38.329 Robert Tseng: The job easier, because we can follow your lead on that, rather than having to go kind of pull a needle out of the haystack.
100 00:18:38.349 ⇒ 00:18:51.979 Robert Tseng: I mean, I’ve seen enough flows that I kind of know where the spots are to look, but, so that definitely helps the second stage of that, where, you know, we’re just basically building hypotheses around where are the biggest drop-offs, how do we validate that with data.
101 00:18:51.979 ⇒ 00:19:00.149 Robert Tseng: Create this feedback loop where, like, you’re able to kind of, like, see if what you think is happening in the users is actually matching their behavior on the platform.
102 00:19:00.599 ⇒ 00:19:18.929 Robert Tseng: Yeah, then the third, the third piece is really, like, okay, now that you have the ability to create great, robust segments based off of drop-off and these, like, we call it behavioral segments, like, what do you want to do next with it? So, sounds like you already have a vision for, kind of, retargeting, both visitors that have dropped off in the funnel.
103 00:19:18.939 ⇒ 00:19:37.239 Robert Tseng: So those are people who have not necessarily signed up or created an account. Maybe they’ve just kind of been kind of in your very, like, in your intake process, and they just… you want to try to identify them and reach them. Then there’s also those who have created an account with you that just haven’t been activated yet, and so you want to kind of
104 00:19:37.239 ⇒ 00:19:44.589 Robert Tseng: you want to have some sequence to go and basically do, like, an onboarding or activation campaign. So, those are definitely kind of,
105 00:19:44.589 ⇒ 00:19:51.549 Robert Tseng: yeah, that’s typically what I would do with a client as well. So, yeah, I think that’s, at a high level, the
106 00:19:51.549 ⇒ 00:19:58.349 Robert Tseng: kind of the different, like, the sequence for how I… how I envisioned that this could possibly work together… possibly work together.
107 00:19:58.359 ⇒ 00:20:00.109 Robert Tseng: But yeah, I wanna… What?
108 00:20:00.110 ⇒ 00:20:04.569 Kat Gillis: That would recommend, the most, if not Pendo.
109 00:20:05.110 ⇒ 00:20:20.589 Robert Tseng: Yeah, well, I would say, I mean, Amplitude is probably the most robust, I think as an industry leader at this point. Yeah. And so, as from, like, a product experience perspective, like, I think they’re probably the best one out there.
110 00:20:20.770 ⇒ 00:20:23.159 Robert Tseng: However, like, I don’t really…
111 00:20:23.350 ⇒ 00:20:34.089 Robert Tseng: I don’t think it’s a huge, urgent thing to decide now. Like, you have to do the DVET data design anyway, and whatever tool you switch. So I would… I would totally recommend just, like.
112 00:20:34.340 ⇒ 00:20:49.029 Robert Tseng: kind of designing the event schema, like, doing this whole, like, the whole, like, discovery strategy piece of it first, and then along the way, if I get to chat with people on your team and better understand how they’re using Pendo, then I can make a better recommendation on whether or not you should switch.
113 00:20:49.290 ⇒ 00:20:55.739 Kat Gillis: Okay, I ask because our Pendo subscription, our renewal is next month.
114 00:20:55.740 ⇒ 00:20:56.310 Robert Tseng: Oh, okay.
115 00:20:56.310 ⇒ 00:20:58.170 Kat Gillis: It’s kind of timely, like…
116 00:20:58.390 ⇒ 00:21:15.310 Kat Gillis: We’re basically committing to another year with them, or switching to something else. My other question is, presumably we do have some time series data in Pendo on these events. Do we lose that when we switch providers?
117 00:21:15.680 ⇒ 00:21:19.209 Robert Tseng: You should be able to migrate everything, kind of,
118 00:21:19.320 ⇒ 00:21:36.479 Robert Tseng: Yeah, event… event data is pretty… I mean, it’s pretty simple. It’s just… it’s just like a timestamp, event name, and then some properties. Those are all pretty, like, agnostic. You can move them anywhere. But my question would be, do you have, like, a data warehouse or any other kind of middle layer that you’re enriching your Pendo data with? Okay.
119 00:21:36.480 ⇒ 00:21:55.629 Kat Gillis: oh, I don’t know if we’re enriching the Pendo data. We do have a data warehouse, and all of that data is sent to Tableau, and then… this is the other problem, is like, half the team then ends up doing random analysis in Tableau, and I’m like, what are we even looking at? So, I’m not… right now, I’m like, I just want a lightweight.
120 00:21:56.050 ⇒ 00:22:04.069 Kat Gillis: tool to start looking at product metrics, and then, you know, eventually marry that with whatever situation is happening in Tableau.
121 00:22:04.510 ⇒ 00:22:07.190 Robert Tseng: Okay, yeah, no, that totally makes sense.
122 00:22:07.570 ⇒ 00:22:22.509 Robert Tseng: Yeah, I think what we find at later stage, once, like, yeah, the product analytics tool can stand up by itself and be effective on its own, once you want to start enriching product data with, like, let’s say… I saw, like, pricing plans and things that you’re doing.
123 00:22:22.510 ⇒ 00:22:36.730 Robert Tseng: So if you’re running pricing experiments, that’s going to come from somewhere else, that’s not really going to come from your product analytics tool. So, like, usually it’s coming from a data warehouse, because that’s where you’re gatekeeping all financial data, and so you can start to enrich data that way.
124 00:22:36.730 ⇒ 00:22:50.439 Robert Tseng: Or, you know, you start to bring in other sources of marketing data. If you have paid ads, and you’re trying to, look at, you know, attribution across different channels that you’re doing, like, so once that starts to become part of the conversation.
125 00:22:50.440 ⇒ 00:22:58.360 Robert Tseng: then I do think, having your product analytics data in your data warehouse to do all of that stitching is very important as well.
126 00:22:58.360 ⇒ 00:23:00.769 Kat Gillis: Okay, that makes sense. Yeah. Yeah, yeah.
127 00:23:01.550 ⇒ 00:23:14.430 Kat Gillis: Okay, investment. What, you know, Upwork just gave an hourly rate, so it’s not super helpful in… when you look at this type of project, how much it typically costs.
128 00:23:14.970 ⇒ 00:23:22.620 Robert Tseng: Yeah, well, I mean, I think for the stage that you’re at, I think we would just do… I mean, I’d do, like, a two-week sprint, probably. Yeah, and we’d do…
129 00:23:22.620 ⇒ 00:23:44.129 Robert Tseng: just the event data design, the strategy piece, and then with the goal of giving you a deliverable on the redesigned tracking schema, also kind of, like, a recommendation on what tooling you should… you should end up with. And I can… I’ll have this all in a one-pager, like, I’ve done enough of these. Yeah, price-wise, we start at $5K, probably just for… I think that’s just, like, an estimate of the bucket of hours it takes to kind of
130 00:23:44.130 ⇒ 00:23:45.439 Robert Tseng: To do this end-to-end.
131 00:23:45.440 ⇒ 00:23:50.559 Robert Tseng: And then, like, staffing-wise, I would put two people on this project, myself and another
132 00:23:50.560 ⇒ 00:24:06.629 Robert Tseng: yeah, probably, like, a senior, like, product analyst that I have on my team. And, yeah, we pretty much just spend time meeting with people, and I guess, however many meetings we can book, and we’ll… we can over the next week or two weeks, and, that… that’s…
133 00:24:06.630 ⇒ 00:24:08.709 Robert Tseng: Generally, what the scope would entail.
134 00:24:09.060 ⇒ 00:24:09.720 Kat Gillis: Okay.
135 00:24:09.790 ⇒ 00:24:10.700 Robert Tseng: Yeah.
136 00:24:10.970 ⇒ 00:24:19.449 Kat Gillis: Cool, that makes sense. Okay, well, I’ll look out for your one-pager, and then I think can go from there.
137 00:24:20.400 ⇒ 00:24:36.510 Robert Tseng: I guess a couple other questions, yeah, in terms of, like, timing-wise, like, sounds like it’s pretty urgent, and, you know, especially if you have this renewal coming up. So, yeah, is this something that you envision kind of making a decision on this week, or kind of where are you at in your, kind of, evaluation? Yeah.
138 00:24:36.510 ⇒ 00:24:50.510 Kat Gillis: Yes, ideally this week, just the numbers that you’ve thrown out already are significantly higher than what we were anticipating paying, so… Okay. I’m gonna need to figure out,
139 00:24:50.510 ⇒ 00:24:57.849 Kat Gillis: yeah, what flexibility, if any, we have. So, that might extend beyond this week, but otherwise, it is urgent, so…
140 00:24:57.850 ⇒ 00:25:12.440 Robert Tseng: Okay. Yeah, I mean, I guess, is there… what budget did you have in mind? Like, is there… I mean, I always kind of… I probably gave you more than what you thought you would come in with, so we can… we could try to see if we can size it down for you, but I just want to get a sense of, like, what are the different levers we have here.
141 00:25:12.600 ⇒ 00:25:20.679 Kat Gillis: Yeah, especially if it… if the output is primarily strategy to start, we had initially budgeted $1,500,
142 00:25:20.680 ⇒ 00:25:21.330 Robert Tseng: Okay.
143 00:25:21.330 ⇒ 00:25:33.730 Kat Gillis: So, the thinking being, okay, from there, you know, presumably we’ll have to pay a little bit more to actually, like, get it into whatever system we’re talking about. Yeah.
144 00:25:33.940 ⇒ 00:25:35.130 Kat Gillis: So…
145 00:25:35.130 ⇒ 00:25:53.819 Robert Tseng: Yeah, I guess, like, what I… yeah, so… I don’t know what your engineering capacity is, but if you want us to do, like, an implementation in that as well, like, we’re happy to do that. What I can do is I can extend it to, you know, once you approve the tracking plan or whatever, then we take, like, you know, the first set of, like.
146 00:25:54.240 ⇒ 00:26:12.149 Robert Tseng: I typically think of it in workflow, so if there’s, like, a single workflow that you do, that’s typically, like, five to seven events, we’ll do the implementation there, in terms of, like, helping you actually put it in, and also I’ll build the reporting out of it, so that way you get to see it end-to-end, and if you’re happy with that, then it’s easier to roll it out across, like, your app, either through
147 00:26:12.150 ⇒ 00:26:17.480 Robert Tseng: you know, your own technical staff, or we could continue to stay on to do that. We do that sometimes as retainer.
148 00:26:17.740 ⇒ 00:26:19.310 Kat Gillis: Yep, okay, that makes sense.
149 00:26:19.310 ⇒ 00:26:28.969 Robert Tseng: So, like, yeah, we have flexibility on, like, whether you want us to kind of go all the way into end, or if you want us to just stay on strategy. I just kind of gave you, like, the full picture of what we could do, yeah.
150 00:26:28.970 ⇒ 00:26:30.009 Kat Gillis: Okay, makes sense.
151 00:26:30.010 ⇒ 00:26:30.560 Robert Tseng: Yeah.
152 00:26:31.130 ⇒ 00:26:31.910 Robert Tseng: Okay.
153 00:26:32.250 ⇒ 00:26:45.710 Robert Tseng: And then lastly, you had mentioned… yeah, who are the people on your team that are kind of, like, hands on keys working with this? Yeah, that, like, would be potential stakeholders to talk to if we were to move forward?
154 00:26:46.710 ⇒ 00:26:52.870 Kat Gillis: So I have a gal on the marketing team who uses primarily the guides. She…
155 00:26:53.170 ⇒ 00:27:04.390 Kat Gillis: She’s very junior, and so wouldn’t be the best to provide input on the marketing data collection that we want to do. I would probably be best suited for that. Okay.
156 00:27:04.610 ⇒ 00:27:24.120 Kat Gillis: But, yeah, she uses the guides. Then, on the product team, I have two PMs. I had a director of product, she just gave notice, but otherwise I would have said she also, you know, whoever is backfilling her, will also have input on the product events.
157 00:27:24.120 ⇒ 00:27:24.450 Robert Tseng: Okay.
158 00:27:24.450 ⇒ 00:27:32.699 Kat Gillis: But there’s one… there’s one PM in particular who knows, kind of, end-to-end the type of stuff that we’re wanting to look at. Yeah.
159 00:27:32.910 ⇒ 00:27:38.079 Kat Gillis: And then… I mean, that’s…
160 00:27:38.770 ⇒ 00:27:51.130 Kat Gillis: Those are the people that’ll probably have the most domain knowledge. We have a data team, and they know about our data lake and the types of things that we store in there, but I’m not sure that we need that in the first phase.
161 00:27:51.600 ⇒ 00:27:52.530 Robert Tseng: Yeah, yeah.
162 00:27:52.940 ⇒ 00:27:53.760 Robert Tseng: Okay.
163 00:27:55.430 ⇒ 00:28:09.910 Robert Tseng: All right, so Sam, I’m hearing, like, possibly 2 or 3 people that we would be able to talk to. Okay, yeah, that gives me an idea. I mean, sometimes there’s, you know, I don’t know how your work’s structured, but sometimes we end up having to schedule, like, five-plus meetings, you know, yeah, so I just wanted to just get a sense of that.
164 00:28:10.430 ⇒ 00:28:16.739 Robert Tseng: Okay, yeah, and then I guess I’ll send you the one-pager, I’ll send you, kind of, yes, this kind of summary of this call.
165 00:28:16.840 ⇒ 00:28:31.650 Robert Tseng: But yeah, like, I think we have flexibility in terms of, like, how much of the scope we have, you want to keep, if you want to size it down. Also, if you want to go hourly instead of fixed, I think fixed is just more off of, like… I mean, generally, I think you probably…
166 00:28:31.830 ⇒ 00:28:40.109 Robert Tseng: It ends up being cheaper and more contained or predictable if you do a fix, but we can have that discussion as well, when you, when you take a look.
167 00:28:40.960 ⇒ 00:28:42.050 Kat Gillis: Great. Cool. That sounds good.
168 00:28:42.050 ⇒ 00:28:46.809 Robert Tseng: Any other questions for me, or kind of things that you worked… that we didn’t cover?
169 00:28:47.290 ⇒ 00:28:49.029 Kat Gillis: No, that all makes sense.
170 00:28:49.730 ⇒ 00:28:54.449 Robert Tseng: Alright, cool. Well then, I’ll shoot that over to you, hopefully by end of the day today.
171 00:28:54.610 ⇒ 00:28:55.690 Kat Gillis: Okay, thank you.
172 00:28:56.030 ⇒ 00:28:56.860 Robert Tseng: Thanks, Cat.
173 00:28:57.050 ⇒ 00:28:57.640 Kat Gillis: Bye.