Meeting Title: Andi Discovery Session Date: 2026-01-12 Meeting participants: Uttam Kumaran, Zoran Selinger, Clarence Stone, Amber Lin
WEBVTT
1 00:00:31.850 ⇒ 00:00:32.950 Uttam Kumaran: Eyes are on.
2 00:00:33.170 ⇒ 00:00:33.860 Zoran Selinger: I’ve done…
3 00:00:34.600 ⇒ 00:00:35.720 Uttam Kumaran: Hey, how are you?
4 00:00:36.320 ⇒ 00:00:37.840 Zoran Selinger: Yeah, a little bit tired.
5 00:00:38.470 ⇒ 00:00:42.030 Zoran Selinger: But… Good overall. What about you?
6 00:00:42.030 ⇒ 00:00:44.000 Uttam Kumaran: What happened? Everything good?
7 00:00:44.630 ⇒ 00:00:52.089 Zoran Selinger: Yeah, yeah, yeah, it’s just, you know, first day back, to kind of regular, regular schedule, so…
8 00:00:52.090 ⇒ 00:00:53.180 Uttam Kumaran: Yes, yes.
9 00:00:53.180 ⇒ 00:00:58.120 Zoran Selinger: Got up, got kids ready, and all of that, so we’re… We were…
10 00:00:58.980 ⇒ 00:01:02.570 Zoran Selinger: We kind of… last two weeks, we were sleeping in a little bit and all that.
11 00:01:02.570 ⇒ 00:01:03.549 Uttam Kumaran: Yeah, yeah, yeah, yeah.
12 00:01:03.550 ⇒ 00:01:06.870 Zoran Selinger: It’ll take a couple of days to get used.
13 00:01:06.870 ⇒ 00:01:14.109 Uttam Kumaran: I feel good, dude. I’m actually finally getting some free time in the day, because, you know, I told operations team, I said.
14 00:01:14.580 ⇒ 00:01:19.590 Uttam Kumaran: your KPI is less than… I need to be in less than 4 hours of meetings per day.
15 00:01:20.380 ⇒ 00:01:29.840 Uttam Kumaran: I said, if we can hit that, I will transform this business. And so, I’m getting… today I had, like, maybe 2 hours of free time, I’m, like, getting…
16 00:01:29.950 ⇒ 00:01:36.090 Uttam Kumaran: I’m getting more available time, which is… which is helpful, so… but yeah, it’s a… It’s been,
17 00:01:36.800 ⇒ 00:01:41.610 Uttam Kumaran: it’s… it’s been tough, like, the last 6 weeks, I feel like it was a lot of work, so…
18 00:01:41.780 ⇒ 00:01:42.210 Zoran Selinger: No.
19 00:01:42.210 ⇒ 00:01:43.350 Uttam Kumaran: Wow, yeah.
20 00:01:46.790 ⇒ 00:01:47.890 Zoran Selinger: Packlines.
21 00:01:47.890 ⇒ 00:01:49.080 Clarence Stone: What’s up?
22 00:01:51.170 ⇒ 00:01:52.790 Zoran Selinger: Is Amber joining us?
23 00:01:53.630 ⇒ 00:01:54.640 Uttam Kumaran: Yes.
24 00:01:58.400 ⇒ 00:01:59.459 Uttam Kumaran: She should be.
25 00:02:02.300 ⇒ 00:02:02.919 Clarence Stone: Sir, were you?
26 00:02:02.920 ⇒ 00:02:04.410 Zoran Selinger: Finally got to play.
27 00:02:04.410 ⇒ 00:02:05.140 Clarence Stone: Good luck.
28 00:02:08.620 ⇒ 00:02:10.900 Zoran Selinger: I finally got to play in cursor.
29 00:02:11.270 ⇒ 00:02:12.049 Zoran Selinger: A little bit.
30 00:02:12.050 ⇒ 00:02:12.910 Uttam Kumaran: Oh, nice.
31 00:02:13.170 ⇒ 00:02:22.690 Zoran Selinger: Yeah, I was talking about… I was talking about Zed in the meeting on… on Friday about this, because I use Zed.
32 00:02:23.110 ⇒ 00:02:29.820 Zoran Selinger: as it’s a little bit… it’s significantly faster on an older laptop, right?
33 00:02:30.950 ⇒ 00:02:43.790 Zoran Selinger: I just tried to get Jupyter notebooks to run properly, just couldn’t. Nice. And, like, okay, I’m just gonna see how it goes on cursor, and everything just works.
34 00:02:44.340 ⇒ 00:02:48.500 Zoran Selinger: It’s so simple, everything just works, so…
35 00:02:48.500 ⇒ 00:02:50.640 Uttam Kumaran: things dead before? Yeah, dude.
36 00:02:51.100 ⇒ 00:02:59.039 Uttam Kumaran: Yeah, I told you. What I… I told you, I’m telling everyone to use cursor, everyone gets on… gets a… gets on… gets to it on their own time, I guess.
37 00:02:59.040 ⇒ 00:03:00.700 Zoran Selinger: Yeah, yeah.
38 00:03:00.700 ⇒ 00:03:05.040 Uttam Kumaran: You know, Amber is a machine on Cursor. Amber does so much.
39 00:03:05.040 ⇒ 00:03:05.670 Zoran Selinger: No.
40 00:03:05.670 ⇒ 00:03:07.540 Uttam Kumaran: She’s, like, the person to copy.
41 00:03:08.760 ⇒ 00:03:12.790 Zoran Selinger: I mean, I’ve used… I’ve used Chrysler a lot over the last…
42 00:03:13.410 ⇒ 00:03:14.969 Uttam Kumaran: analysis, It’s popular.
43 00:03:15.410 ⇒ 00:03:16.549 Zoran Selinger: Yeah, like…
44 00:03:16.550 ⇒ 00:03:17.310 Uttam Kumaran: Yeah.
45 00:03:17.690 ⇒ 00:03:26.499 Zoran Selinger: But I kind of switched to, let’s… I saw Zed tried, and it really is significantly faster, but they just…
46 00:03:27.000 ⇒ 00:03:33.180 Zoran Selinger: For notebooks in particular, now we just… cursor just works.
47 00:03:33.760 ⇒ 00:03:34.410 Uttam Kumaran: Yes.
48 00:03:34.410 ⇒ 00:03:37.939 Zoran Selinger: I got to play with it today, signi- like.
49 00:03:38.240 ⇒ 00:03:42.879 Uttam Kumaran: basically 5 hours, and I enjoyed it very much.
50 00:03:44.480 ⇒ 00:03:56.389 Zoran Selinger: And this switch of, like, you showing us to actually do, like, the client comms, prepare it there, it just… that suits me so well. I want to be in the editor as much as I can.
51 00:03:56.390 ⇒ 00:03:59.959 Uttam Kumaran: Me too, dude, me too!
52 00:04:00.970 ⇒ 00:04:01.400 Zoran Selinger: It’s a…
53 00:04:01.400 ⇒ 00:04:07.579 Uttam Kumaran: That’s why I like our company, because, like, everybody’s, like, mostly engineers, so, like, nobody will be like, oh, it’s too, like, technical, it’s…
54 00:04:07.580 ⇒ 00:04:08.620 Zoran Selinger: Yeah, yeah, yeah.
55 00:04:08.740 ⇒ 00:04:13.470 Uttam Kumaran: I just don’t want… I, dude, I want to run my whole life in person. I don’t want to do anything else.
56 00:04:17.829 ⇒ 00:04:18.639 Zoran Selinger: Yeah.
57 00:04:19.120 ⇒ 00:04:21.880 Uttam Kumaran: Okay, maybe we can get started. I pinged Amber, but…
58 00:04:22.920 ⇒ 00:04:24.249 Zoran Selinger: Well, I guess, yeah.
59 00:04:24.680 ⇒ 00:04:32.239 Uttam Kumaran: Yeah, so maybe we can run through… yeah, I’m… my interest is to hear about GA stuff, so yeah, you can tell me where…
60 00:04:32.550 ⇒ 00:04:35.670 Uttam Kumaran: where we want to begin, but yeah, that’s what I’m kind of interested in.
61 00:04:35.990 ⇒ 00:04:40.849 Zoran Selinger: Yeah, let me just go through a document a little bit.
62 00:04:41.460 ⇒ 00:04:47.710 Zoran Selinger: I was… Like, some things look really good,
63 00:04:48.390 ⇒ 00:04:50.879 Zoran Selinger: But then, for example, we don’t have
64 00:04:51.440 ⇒ 00:04:58.900 Zoran Selinger: And that’s nature of the business, it’s maybe hard to track, but we, for example, we don’t have any revenue numbers in there.
65 00:05:02.340 ⇒ 00:05:04.750 Zoran Selinger: So it’s not… it’s not perfect.
66 00:05:05.890 ⇒ 00:05:12.510 Zoran Selinger: But they mostly do a good job. I’m just talking about, kind of technical implementation. We do have
67 00:05:13.020 ⇒ 00:05:14.860 Zoran Selinger: We do have stuff in there.
68 00:05:18.100 ⇒ 00:05:22.850 Uttam Kumaran: Yeah, so, yeah, also, I think, Clarence, I just want you to, for your awareness, this is just basically, like.
69 00:05:22.980 ⇒ 00:05:25.450 Uttam Kumaran: what’s in GA, and…
70 00:05:25.830 ⇒ 00:05:36.509 Uttam Kumaran: it’s like, look, one big thing is just, like, is GA in a good… in a good place? And then also, like, what features or whatever are they using? And next is also, like, okay, what do we see? Like…
71 00:05:36.510 ⇒ 00:05:38.030 Zoran Selinger: You know?
72 00:05:38.930 ⇒ 00:05:43.769 Zoran Selinger: Yeah, so… First I was looking at… how close…
73 00:05:44.360 ⇒ 00:05:46.580 Zoran Selinger: How can I zoom this properly?
74 00:05:47.770 ⇒ 00:05:54.000 Zoran Selinger: So, first I was looking at the channels, are you seeing the document?
75 00:05:54.440 ⇒ 00:05:55.230 Uttam Kumaran: Yes.
76 00:05:55.760 ⇒ 00:06:09.690 Zoran Selinger: Cool. Obviously, I was looking at channels, so basically, I’m focused on anything… anything that’s in the session scope. I wanted to see the engagement, and I wanted to see conversion rates.
77 00:06:09.800 ⇒ 00:06:16.339 Zoran Selinger: Both of those things are good, so we have engagement… engaged sessions tracked properly.
78 00:06:16.460 ⇒ 00:06:23.679 Zoran Selinger: So I can get good engagement rates, but also, we have 4… we have 4 events that are tracked in there.
79 00:06:24.600 ⇒ 00:06:26.999 Zoran Selinger: And that’s, the lead.
80 00:06:27.740 ⇒ 00:06:35.299 Zoran Selinger: phone call purchase and a form submission. So I was looking at conversion rates of those form events… oh, of those four events.
81 00:06:36.770 ⇒ 00:06:47.480 Zoran Selinger: For our session metrics. I have to say, so it absolutely… a clear winner is organic.
82 00:06:48.510 ⇒ 00:06:50.480 Zoran Selinger: Organic is both…
83 00:06:51.070 ⇒ 00:06:55.479 Zoran Selinger: No, we’re so… wait, we’re just seeing your, we’re seeing your, just your Gmail.
84 00:06:55.980 ⇒ 00:06:56.839 Zoran Selinger: I’m sorry.
85 00:06:57.190 ⇒ 00:06:58.920 Uttam Kumaran: I was looking at the doc.
86 00:07:00.250 ⇒ 00:07:03.120 Zoran Selinger: Oh, you’re… you’re looking at your screen.
87 00:07:04.820 ⇒ 00:07:07.590 Clarence Stone: Damn, I’m looking at my thing, I didn’t notice what you were sharing.
88 00:07:10.380 ⇒ 00:07:15.909 Zoran Selinger: Yeah, so… Organic is an absolute winner for them.
89 00:07:17.370 ⇒ 00:07:36.019 Zoran Selinger: both in the, in the volume and in performance. So, the best engagement, basically, and also conversion rates are up to par with all the other, all the other, high, high traffic, channels.
90 00:07:36.220 ⇒ 00:07:40.810 Zoran Selinger: So… We… like, it’s a clear winner.
91 00:07:41.260 ⇒ 00:07:53.040 Zoran Selinger: they should continue… they’re doing a really good job at organic, and they should do more of it, right? And we talked to the… to the… what’s the… was it Joe? What’s the… what was… what’s his name?
92 00:07:54.210 ⇒ 00:08:02.909 Zoran Selinger: they know what they’re doing on organic, they are thinking about, AI as well, how to adjust it for, for.
93 00:08:03.720 ⇒ 00:08:05.579 Zoran Selinger: For the engines, and…
94 00:08:05.700 ⇒ 00:08:14.679 Zoran Selinger: Yeah, they’re on… they know what they’re doing there, and they should continue doing so. There’s quite a bit of paid search volume as well.
95 00:08:16.210 ⇒ 00:08:16.740 Zoran Selinger: From where?
96 00:08:16.980 ⇒ 00:08:18.679 Zoran Selinger: From what, like, what channel?
97 00:08:19.370 ⇒ 00:08:20.330 Zoran Selinger: paid search.
98 00:08:21.250 ⇒ 00:08:23.760 Uttam Kumaran: No, but… I mean, that kind of volume…
99 00:08:23.760 ⇒ 00:08:28.220 Zoran Selinger: you can, yeah, you can get, at least in US,
100 00:08:28.390 ⇒ 00:08:34.269 Zoran Selinger: Basically only from Google. So it’s,
101 00:08:35.030 ⇒ 00:08:40.459 Zoran Selinger: It’s… engagement rate and conversion rates are decent, they are below, below organic.
102 00:08:41.000 ⇒ 00:08:47.840 Zoran Selinger: But they are, are decent. We have, we have…
103 00:08:48.520 ⇒ 00:08:52.050 Zoran Selinger: A problem, a potential, with direct
104 00:08:52.820 ⇒ 00:08:57.470 Zoran Selinger: Where we have, quite a lower engagement rate.
105 00:08:58.560 ⇒ 00:09:00.439 Zoran Selinger: In direct traffic.
106 00:09:01.150 ⇒ 00:09:04.289 Zoran Selinger: And you will see later that… that kind of…
107 00:09:04.290 ⇒ 00:09:07.179 Uttam Kumaran: What is that, sorry, what is engagement rate defined as?
108 00:09:08.410 ⇒ 00:09:17.459 Zoran Selinger: The engagement rate is where you had, where you had, multiple page views and or, events in a session.
109 00:09:17.640 ⇒ 00:09:20.170 Uttam Kumaran: Okay, okay, so it’s like an active session, but you haven’t…
110 00:09:20.170 ⇒ 00:09:21.110 Zoran Selinger: session, yeah, yeah.
111 00:09:21.110 ⇒ 00:09:26.610 Uttam Kumaran: You didn’t do anything that looks at, conversion, yeah, right?
112 00:09:26.610 ⇒ 00:09:27.540 Zoran Selinger: Yeah, I did, I did.
113 00:09:27.540 ⇒ 00:09:28.970 Uttam Kumaran: Okay, okay, okay, okay, we’re getting there, good.
114 00:09:28.970 ⇒ 00:09:36.430 Zoran Selinger: We have conversion rates for, basically, I have conversion rates for channels, landing pages, cities, age, gender.
115 00:09:36.560 ⇒ 00:09:41.039 Uttam Kumaran: And then what is the… but what is conversion defined as? Like, that they’re doing a checkout?
116 00:09:41.880 ⇒ 00:09:42.590 Uttam Kumaran: Her schedule?
117 00:09:42.590 ⇒ 00:09:49.209 Zoran Selinger: So conversion… so, a generate lead conversion rate would… rate would be…
118 00:09:49.460 ⇒ 00:09:56.240 Zoran Selinger: a session dot where someone converted into. So, when it triggered a generate lead.
119 00:09:56.240 ⇒ 00:10:02.649 Uttam Kumaran: And they, and, and they, Monkey Boy, they set, they set the conversion events up.
120 00:10:03.050 ⇒ 00:10:03.790 Zoran Selinger: Yes.
121 00:10:03.790 ⇒ 00:10:05.219 Uttam Kumaran: Okay, okay, okay, okay, so one thing…
122 00:10:05.220 ⇒ 00:10:07.789 Zoran Selinger: Conversion events are in there, yes.
123 00:10:07.790 ⇒ 00:10:12.950 Uttam Kumaran: There are more than those four, but I thought those four are the most relevant.
124 00:10:14.150 ⇒ 00:10:19.990 Uttam Kumaran: Yeah, I guess one point for me is just to understand, like, if those are accurate. Like.
125 00:10:20.220 ⇒ 00:10:22.689 Uttam Kumaran: Right, so we can go through and just make sure
126 00:10:23.050 ⇒ 00:10:26.159 Uttam Kumaran: Those conversion events are firing? Yeah, expected, you know?
127 00:10:26.160 ⇒ 00:10:30.640 Zoran Selinger: So then we’re talking about a kind of technical audit, technical implementation audit.
128 00:10:30.790 ⇒ 00:10:35.370 Zoran Selinger: And obviously, yeah, we can… we can do that, but that’s a,
129 00:10:35.460 ⇒ 00:10:51.319 Zoran Selinger: I wouldn’t call… I mean, I don’t know… I didn’t understand what the discovery is. I hear you, I hear you, I hear you. I’m looking for insights right now into, you know, channels and how things look, but if you want to have a, like, a technical deep dive, of course.
130 00:10:51.420 ⇒ 00:10:55.709 Zoran Selinger: But I would… You know, I would charge for that work. I…
131 00:10:55.710 ⇒ 00:10:58.969 Uttam Kumaran: I hear you, I hear you.
132 00:10:58.970 ⇒ 00:11:02.769 Zoran Selinger: You’ll see there are obvious issues.
133 00:11:03.590 ⇒ 00:11:06.980 Zoran Selinger: With, like, technical issues with implementation.
134 00:11:08.090 ⇒ 00:11:09.600 Uttam Kumaran: You’ll see, like.
135 00:11:09.690 ⇒ 00:11:17.090 Zoran Selinger: cities that are outside of the service area being tracked, you’ll see a lot of, a lot of…
136 00:11:17.090 ⇒ 00:11:17.860 Uttam Kumaran: Oh, okay.
137 00:11:17.860 ⇒ 00:11:21.979 Zoran Selinger: evidence of potential bots in there and stuff like that. There’s a lot here.
138 00:11:21.980 ⇒ 00:11:23.759 Uttam Kumaran: Okay. Okay, okay, okay.
139 00:11:23.760 ⇒ 00:11:26.869 Zoran Selinger: Yeah, yeah, yeah. So, you see,
140 00:11:27.120 ⇒ 00:11:30.120 Zoran Selinger: Conversion rates are, you know, decent.
141 00:11:30.490 ⇒ 00:11:46.870 Zoran Selinger: for… for leads, and… and phone calls and all… purchases are… I don’t know what purchases mean… mean exactly for them. There are very few in there. I think, like, 200 of them tracked in a year. So I don’t know exactly what that means.
142 00:11:47.200 ⇒ 00:11:47.790 Uttam Kumaran: Okay.
143 00:11:48.040 ⇒ 00:11:58.539 Uttam Kumaran: Yeah, I wanna… I wanna… we can create a little bit of a glossary also on, like, purchase versus conversion, because client is not gonna know, Monkey Boy will know. They do sell some, like.
144 00:11:58.680 ⇒ 00:12:02.889 Uttam Kumaran: things on their site, so that may be it, but okay, understood.
145 00:12:03.500 ⇒ 00:12:05.070 Zoran Selinger: Yeah.
146 00:12:05.570 ⇒ 00:12:06.540 Uttam Kumaran: So…
147 00:12:06.980 ⇒ 00:12:14.069 Zoran Selinger: Yeah, organic… organic kills it. We have, unassigned is very interesting.
148 00:12:14.220 ⇒ 00:12:17.550 Uttam Kumaran: How is their organic so high, dude? Where does it… what are the channels?
149 00:12:20.080 ⇒ 00:12:21.489 Zoran Selinger: Oh, I don’t mean, wire channels?
150 00:12:21.490 ⇒ 00:12:23.400 Uttam Kumaran: Like, when is the sources? Sorry.
151 00:12:23.940 ⇒ 00:12:27.540 Zoran Selinger: Oh, for organic, I mean, it’s… it’s basically all Google.
152 00:12:28.660 ⇒ 00:12:30.020 Zoran Selinger: Okay.
153 00:12:30.020 ⇒ 00:12:32.629 Uttam Kumaran: Well, but are you sure it’s Google My Business?
154 00:12:34.020 ⇒ 00:12:36.599 Zoran Selinger: Oh, or it’s… no, no, I’m not sure.
155 00:12:36.600 ⇒ 00:12:41.970 Uttam Kumaran: Okay, okay, okay. Because they have a huge, they have a huge presence on Google My Business.
156 00:12:42.410 ⇒ 00:12:58.339 Zoran Selinger: And that is evident from later when we… when I show you the regon for cities, and the funnels for cities, they… they work really well. So the landing pages for particular, like, locat… their location marketing.
157 00:12:58.340 ⇒ 00:12:59.830 Uttam Kumaran: Location-based, yeah, yeah.
158 00:12:59.830 ⇒ 00:13:00.990 Zoran Selinger: is very good.
159 00:13:01.140 ⇒ 00:13:07.829 Uttam Kumaran: So it’s all… that’s all gonna be Google My Business, because people, for example, these guys are a home service, so you’re like.
160 00:13:08.080 ⇒ 00:13:10.629 Uttam Kumaran: There’s a raccoon in my garage.
161 00:13:10.630 ⇒ 00:13:19.270 Zoran Selinger: I live in Austin. I need raccoon Help Austin, you know? So it’s very… so typically, these are, like, very, like, timely purchases.
162 00:13:19.330 ⇒ 00:13:32.330 Uttam Kumaran: And they have a really impressive Google My Business. I think they’re almost at 5,000 reviews, and they have Google My Business set up, Google Business for several… for almost every single one of their
163 00:13:32.400 ⇒ 00:13:40.919 Uttam Kumaran: branches, you know, so they’re able to get really good reviews, and it’s, like, direct traffic. But I also think there’s optimization there, you know?
164 00:13:41.460 ⇒ 00:13:56.990 Zoran Selinger: Sure, sure. So, I wanted to emphasize this. So, this unassigned actually has a really high conversion rate for phone calls, and when I looked at what’s unassigned, basically something called
165 00:13:57.250 ⇒ 00:14:02.890 Zoran Selinger: Calcone, Saltz, I don’t know how to read this, display retargeted.
166 00:14:02.890 ⇒ 00:14:04.380 Uttam Kumaran: Alcon, oh, okay.
167 00:14:04.810 ⇒ 00:14:10.320 Zoran Selinger: So they are killing it with that traffic source, when it comes to phone calls.
168 00:14:10.500 ⇒ 00:14:11.710 Uttam Kumaran: Oh, okay.
169 00:14:11.710 ⇒ 00:14:19.990 Zoran Selinger: Yeah, it’s running into unassigned in Google Analytics, but that’s what it is. Basically, the whole unassigned bucket is that one traffic source.
170 00:14:20.160 ⇒ 00:14:21.210 Uttam Kumaran: Oh, interesting, okay.
171 00:14:21.210 ⇒ 00:14:23.599 Zoran Selinger: Yeah, so they’re killing it with that.
172 00:14:23.740 ⇒ 00:14:27.779 Zoran Selinger: So, landing pages, obviously, you know.
173 00:14:28.260 ⇒ 00:14:32.960 Zoran Selinger: still, for traffic, it’s the homepage.
174 00:14:33.900 ⇒ 00:14:50.380 Zoran Selinger: And then, pest control is, is the third. But they have, like, location-specific, pages are very good engagement, very good conversion rates as well. So they’re really doing well on the, on the local, local stuff.
175 00:14:50.680 ⇒ 00:14:54.980 Zoran Selinger: So that’s very, very interesting.
176 00:14:54.980 ⇒ 00:15:05.300 Uttam Kumaran: But we… but we’re… but we’re looking… I guess engagement rate, I guess more of what we’d be looking for is, like, what’s going on with conversion, right? So, like, where is the opportunity on the conversion side?
177 00:15:05.950 ⇒ 00:15:09.579 Uttam Kumaran: Because if the engagement rate’s good, that’s good. People are coming, they have high intent.
178 00:15:10.380 ⇒ 00:15:12.739 Uttam Kumaran: But then maybe they’re not converting, you know?
179 00:15:13.460 ⇒ 00:15:14.100 Zoran Selinger: Yeah.
180 00:15:14.210 ⇒ 00:15:23.329 Zoran Selinger: So, here, when we’re looking at it, when it comes to the specific service, pest control is the strongest,
181 00:15:23.450 ⇒ 00:15:32.209 Zoran Selinger: Totally. And then, when it comes to landing pages, it’s basically location landing pages that are performing the best.
182 00:15:32.730 ⇒ 00:15:34.639 Zoran Selinger: You can just compare…
183 00:15:34.640 ⇒ 00:15:35.260 Uttam Kumaran: Okay.
184 00:15:35.260 ⇒ 00:15:39.060 Zoran Selinger: So none of the other ones are really… Anything else?
185 00:15:39.120 ⇒ 00:15:41.010 Uttam Kumaran: Okay, okay, great.
186 00:15:41.850 ⇒ 00:15:45.590 Zoran Selinger: So that’s gonna, do the best,
187 00:15:46.860 ⇒ 00:15:56.489 Zoran Selinger: phone call, critical anomaly, you see here? For, so, for the landing page.
188 00:15:57.870 ⇒ 00:16:03.110 Zoran Selinger: Like, anything not set, so this is potentially, bot traffic, okay?
189 00:16:03.110 ⇒ 00:16:04.429 Uttam Kumaran: Oh, okay, okay.
190 00:16:04.430 ⇒ 00:16:10.139 Zoran Selinger: that is click… that is clicking into phone numbers. So, some kind of bot.
191 00:16:10.140 ⇒ 00:16:11.729 Uttam Kumaran: So, there’s a lot of…
192 00:16:11.860 ⇒ 00:16:16.829 Zoran Selinger: a lot of indication that they deal with this quite a lot in there.
193 00:16:17.390 ⇒ 00:16:19.749 Zoran Selinger: So for purchases, yeah.
194 00:16:20.160 ⇒ 00:16:28.469 Zoran Selinger: For the form, again, just a location-specific kills it there. What’s next? What’s next?
195 00:16:28.900 ⇒ 00:16:39.130 Zoran Selinger: Cities… Very, very similar in terms of engagement rate, but let’s scroll to the conversions.
196 00:16:39.600 ⇒ 00:16:46.459 Zoran Selinger: conversion rate, Austin, Houston, San Antonio, and you’ll see, you’ll see the funnels later.
197 00:16:47.940 ⇒ 00:16:52.490 Uttam Kumaran: I also pulled funnels for those locations. Right, okay.
198 00:16:52.660 ⇒ 00:16:53.360 Zoran Selinger: Yeah.
199 00:16:53.640 ⇒ 00:16:54.280 Zoran Selinger: So…
200 00:16:54.280 ⇒ 00:16:59.639 Uttam Kumaran: So one thing that could be helpful, and I don’t know if you’ve ever done this, but, like, for me, it’s almost interesting to see, like.
201 00:17:00.050 ⇒ 00:17:06.810 Uttam Kumaran: All the different ways that people purchase the service, and to kind of understand the conversion rates by
202 00:17:06.910 ⇒ 00:17:08.430 Uttam Kumaran: Basically, like, funnel.
203 00:17:08.730 ⇒ 00:17:12.260 Uttam Kumaran: And then you look at, okay, like, which ones are already optimized versus.
204 00:17:12.640 ⇒ 00:17:14.280 Zoran Selinger: Which ones are not, right?
205 00:17:14.680 ⇒ 00:17:28.559 Zoran Selinger: So, when we talk about… let’s skip to… so we have a little bit of age. Basically, demographic data in terms of age and gender in Google Analytics is always going to be mostly unknown.
206 00:17:29.040 ⇒ 00:17:35.859 Zoran Selinger: It’s very rare that you get a small unknown bucket in Google Analytics.
207 00:17:36.040 ⇒ 00:17:37.020 Uttam Kumaran: Okay, okay.
208 00:17:37.020 ⇒ 00:17:39.400 Zoran Selinger: So what you see here is very normal, that you.
209 00:17:39.400 ⇒ 00:17:41.840 Uttam Kumaran: But what do you recommend people do?
210 00:17:42.570 ⇒ 00:17:43.320 Zoran Selinger: Fantastic.
211 00:17:44.130 ⇒ 00:17:44.650 Zoran Selinger: What do you mean?
212 00:17:44.650 ⇒ 00:17:47.399 Uttam Kumaran: Like, to improve, to increase the enrichment.
213 00:17:48.240 ⇒ 00:17:48.970 Uttam Kumaran: like…
214 00:17:48.970 ⇒ 00:17:53.860 Zoran Selinger: With Google Analytics, no, I don’t think that’s gonna be,
215 00:17:54.750 ⇒ 00:18:07.790 Zoran Selinger: So you typically recommend you have to… You’re better relying… I mean, if you are, for example, in… if you’re advertising on Facebook, on Meta, that’s really reliable, good data, in terms of…
216 00:18:07.790 ⇒ 00:18:08.670 Uttam Kumaran: Okay, okay.
217 00:18:08.670 ⇒ 00:18:11.699 Zoran Selinger: It’s way, way better than anything that Google can provide.
218 00:18:12.340 ⇒ 00:18:23.919 Zoran Selinger: I hear you. Simply because we do volunteer all that data very clearly in a structured way on social networks, as opposed to, you know.
219 00:18:23.920 ⇒ 00:18:25.069 Uttam Kumaran: Browser, yeah.
220 00:18:25.070 ⇒ 00:18:31.219 Zoran Selinger: So, yeah, that’s always gonna be more, more accurate in there anyway. Okay.
221 00:18:31.220 ⇒ 00:18:40.939 Uttam Kumaran: Sorry, I’m gonna jump around again. You said that there was paid search volume… oh, but paid search is all Google, but you don’t see any… you shouldn’t see much in terms of paid advertising.
222 00:18:41.180 ⇒ 00:18:45.690 Uttam Kumaran: like, traditional… Digital paid advertising, right?
223 00:18:46.760 ⇒ 00:18:57.750 Zoran Selinger: So I… so they have, like, a paid search bucket, right, to me. So I did not look into very specific,
224 00:18:58.040 ⇒ 00:19:03.160 Zoran Selinger: session, like, source-medium combinations. Okay. But that’s…
225 00:19:03.160 ⇒ 00:19:06.110 Uttam Kumaran: I guess, like, you didn’t see anything from, like, TikTok?
226 00:19:07.470 ⇒ 00:19:08.620 Uttam Kumaran: Facebook.
227 00:19:09.430 ⇒ 00:19:16.440 Zoran Selinger: I mean, they have, they have, in the channels, they have social… But you…
228 00:19:16.440 ⇒ 00:19:16.760 Uttam Kumaran: Dave.
229 00:19:16.760 ⇒ 00:19:22.099 Zoran Selinger: That they have paid social, they have organic and paid social in there, so they are actively doing…
230 00:19:22.930 ⇒ 00:19:26.830 Uttam Kumaran: Okay, I’m interested, maybe we can go to the ad library and see what’s going on, you know?
231 00:19:27.780 ⇒ 00:19:32.290 Zoran Selinger: I mean, yeah, if you can get access to them, or…
232 00:19:33.520 ⇒ 00:19:41.550 Zoran Selinger: Obviously, that’s gonna be great. Okay. Well, that’s age, so you have, they perform pre…
233 00:19:41.790 ⇒ 00:19:52.129 Zoran Selinger: there’s not a lot of difference in age brackets at all when it comes to conversion rates, you see? There’s nothing that really sticks out there.
234 00:19:53.450 ⇒ 00:19:57.600 Zoran Selinger: And this is gender…
235 00:19:57.880 ⇒ 00:20:04.310 Zoran Selinger: Very, very similar in all three… all three buckets, and now we get to the click-to-buy.
236 00:20:04.730 ⇒ 00:20:05.500 Zoran Selinger: Okay?
237 00:20:05.980 ⇒ 00:20:06.620 Uttam Kumaran: Yes.
238 00:20:07.030 ⇒ 00:20:13.400 Zoran Selinger: Yeah, so it’s mostly the same. For some reason, Dallas is not properly tracked.
239 00:20:14.470 ⇒ 00:20:20.219 Zoran Selinger: Unfortunately, it’s such a big and important location, and it’s not properly tracked.
240 00:20:20.580 ⇒ 00:20:38.139 Zoran Selinger: I don’t know, we don’t have click-to-buy Dallas pages in the funnel. So we have a really clear starting, then service selection, order review, checkout, and completed purchase. We have a really clear funnel in the click-to-buy, and
241 00:20:38.370 ⇒ 00:20:44.009 Zoran Selinger: It’s set up correctly, and these are the drop-off rates on each… each of the steps.
242 00:20:44.170 ⇒ 00:20:45.110 Zoran Selinger: Okay?
243 00:20:45.210 ⇒ 00:20:46.769 Zoran Selinger: So once we get…
244 00:20:46.770 ⇒ 00:20:47.220 Uttam Kumaran: Brutal.
245 00:20:47.220 ⇒ 00:20:50.279 Zoran Selinger: to checkout, we are pretty good, you know?
246 00:20:50.560 ⇒ 00:20:59.279 Zoran Selinger: we only drop about 16, 19, 20% of the people online. But dude, order review is crazy. What is order review?
247 00:21:00.880 ⇒ 00:21:05.269 Zoran Selinger: That, that is crazy, yes. So that’s something to… Holy shit.
248 00:21:05.640 ⇒ 00:21:07.849 Clarence Stone: Tom, is that where they select the date?
249 00:21:11.030 ⇒ 00:21:15.000 Zoran Selinger: I think they all… yeah, they already go through, through a form.
250 00:21:15.350 ⇒ 00:21:19.179 Uttam Kumaran: No, no, no, that’s not the date… that’s not the date, I think. Or maybe.
251 00:21:19.490 ⇒ 00:21:20.499 Uttam Kumaran: I don’t know.
252 00:21:21.380 ⇒ 00:21:24.840 Zoran Selinger: I think they’re past the form already at this stage.
253 00:21:24.840 ⇒ 00:21:28.969 Uttam Kumaran: Well, Zoran, you have the video of me purchasing, so you can map it also.
254 00:21:29.340 ⇒ 00:21:30.470 Zoran Selinger: Okay, okay.
255 00:21:31.250 ⇒ 00:21:35.220 Uttam Kumaran: Because I bought… I bought two… I bought through Click to Buy, and I bought through online scheduling.
256 00:21:36.780 ⇒ 00:21:39.249 Uttam Kumaran: So you have… we’ll end up having that.
257 00:21:39.790 ⇒ 00:21:47.430 Zoran Selinger: Yeah, okay. And it’s the same for every location at this step, you know?
258 00:21:47.670 ⇒ 00:21:58.640 Zoran Selinger: the graph looks… look very, very similar, for those, you see, this 50-60% drop-off at the… at the order review, is, yeah, it’s…
259 00:21:58.750 ⇒ 00:22:07.379 Zoran Selinger: It’s… it’s a lot. You see, San Antonio has, higher drop-off rates at the checkout and the purchase step.
260 00:22:08.130 ⇒ 00:22:19.119 Zoran Selinger: Dallas, unfortunately, it’s such an important location, they need to fix this. We don’t have clear visibility, at least not in Google Analytics on Dallas.
261 00:22:19.440 ⇒ 00:22:23.759 Zoran Selinger: So this is, this is broken,
262 00:22:24.430 ⇒ 00:22:36.369 Zoran Selinger: Corpus Christi is crazy. It’s significantly higher than other locations, and it’s a huge location for them, and drop-off rates are really, really, really.
263 00:22:36.370 ⇒ 00:22:37.920 Uttam Kumaran: Wow. Oh my god.
264 00:22:37.920 ⇒ 00:22:41.310 Zoran Selinger: Yeah, this is a really problematic location.
265 00:22:41.770 ⇒ 00:22:42.360 Zoran Selinger: And…
266 00:22:42.360 ⇒ 00:22:46.430 Uttam Kumaran: Dude, even the funnel sessions, yeah, it’s crazy, oh my gosh.
267 00:22:47.080 ⇒ 00:22:47.640 Zoran Selinger: Yeah.
268 00:22:48.760 ⇒ 00:22:49.900 Zoran Selinger: So that’s something.
269 00:22:49.900 ⇒ 00:22:53.030 Uttam Kumaran: I’m gonna cry, I’m gonna cry of looking at this.
270 00:22:53.780 ⇒ 00:22:54.910 Uttam Kumaran: It’s crazy.
271 00:22:55.820 ⇒ 00:22:58.960 Zoran Selinger: And Fort Worth is also broken, we don’t have
272 00:22:59.860 ⇒ 00:23:07.530 Zoran Selinger: we don’t have, proper steps there for click-to-buy. I wonder why, because it…
273 00:23:07.840 ⇒ 00:23:10.249 Zoran Selinger: It doesn’t seem like it’s a…
274 00:23:10.840 ⇒ 00:23:21.700 Zoran Selinger: I almost don’t think it’s a… it’s a bug, but there’s some… there’s… there is a reason for it, and it’ll be good to understand what it is.
275 00:23:21.830 ⇒ 00:23:29.300 Zoran Selinger: I don’t know if they provide different type of service, or… or there’s a special,
276 00:23:29.770 ⇒ 00:23:33.390 Zoran Selinger: It’s a different funnel for those two cities.
277 00:23:34.320 ⇒ 00:23:35.320 Zoran Selinger: Not sure.
278 00:23:37.580 ⇒ 00:23:53.849 Zoran Selinger: Yeah, so that’s… that’s it for now. I see you are interested, more in, like, in more detail about specific traffic sources, not just grouped at channels, but maybe going one… one step deeper, so I can look into that.
279 00:23:55.030 ⇒ 00:23:56.410 Uttam Kumaran: Yeah, I mean, I think, like…
280 00:23:56.500 ⇒ 00:23:57.870 Zoran Selinger: What’s your…
281 00:23:57.870 ⇒ 00:24:00.759 Uttam Kumaran: What is your gut inst… like, do you think you have a sense of, like.
282 00:24:01.270 ⇒ 00:24:10.349 Uttam Kumaran: low-hanging fruit… I mean, there’s some tracking things we have to clear first, right? And then the second piece is, like, maybe it’s easier for us to affect
283 00:24:10.460 ⇒ 00:24:15.759 Uttam Kumaran: The conversion rate before affecting traffic, you know, because I don’t know…
284 00:24:16.960 ⇒ 00:24:22.240 Zoran Selinger: For sure, I mean, this… This drop-off rates specifically.
285 00:24:22.670 ⇒ 00:24:28.200 Zoran Selinger: this is, like, these two… two first steps, like, this is good.
286 00:24:29.180 ⇒ 00:24:47.349 Zoran Selinger: this is fine, 15% drop-off. Obviously, we can… and I think they do a good, good job at the retargeting that we saw earlier, that is in an attributed channel. So that’s probably picking a lot of these.
287 00:24:47.640 ⇒ 00:24:48.720 Zoran Selinger: as well.
288 00:24:49.600 ⇒ 00:24:50.290 Uttam Kumaran: Yes.
289 00:24:50.290 ⇒ 00:24:51.480 Zoran Selinger: This is not good.
290 00:24:53.450 ⇒ 00:24:56.869 Zoran Selinger: This, we can… we can impact this, for sure.
291 00:24:58.170 ⇒ 00:25:01.259 Zoran Selinger: So that’s the low-hanging fruit, I would say.
292 00:25:02.580 ⇒ 00:25:04.479 Zoran Selinger: Just look at the difference here.
293 00:25:04.870 ⇒ 00:25:12.809 Clarence Stone: So are you curious to see what service, led to the checkout? Like, it’d be really good to see the breakdown by service as well.
294 00:25:14.510 ⇒ 00:25:17.680 Zoran Selinger: I’ll have to see if they…
295 00:25:18.240 ⇒ 00:25:20.730 Zoran Selinger: If they have this type of data.
296 00:25:21.220 ⇒ 00:25:23.730 Clarence Stone: Yeah, it doesn’t, it doesn’t, right? It’s another.
297 00:25:23.730 ⇒ 00:25:26.760 Zoran Selinger: Yeah, these are… these are URL-based.
298 00:25:27.750 ⇒ 00:25:39.539 Zoran Selinger: And these are URL-based funnels, so they are very, very super clear, right? They have a, like, an Austin in a URL. It’s a… it’s 100% that’s the funnel.
299 00:25:39.990 ⇒ 00:25:48.479 Zoran Selinger: To get, by service, there might be something in the events and event properties where we could build a funnel.
300 00:25:48.850 ⇒ 00:25:54.730 Zoran Selinger: But yeah, I’d have to look into that. I can, I can look into that.
301 00:25:56.770 ⇒ 00:26:03.460 Clarence Stone: So, for some background, Zoran, not all the same services are offered at all the same locations.
302 00:26:04.210 ⇒ 00:26:07.439 Clarence Stone: Dallas and Fort Worth, and they have a lot less services.
303 00:26:09.430 ⇒ 00:26:18.440 Clarence Stone: And hey, Utam, wasn’t Dallas the region they were talking about, where it’s on a different, management platform entirely?
304 00:26:20.230 ⇒ 00:26:22.600 Uttam Kumaran: Yeah, so it could be… that could be the reason.
305 00:26:22.820 ⇒ 00:26:23.470 Zoran Selinger: Yeah.
306 00:26:24.380 ⇒ 00:26:29.880 Zoran Selinger: That’s what I said, it doesn’t seem to me like they would miss it for this to be a bug.
307 00:26:30.320 ⇒ 00:26:30.700 Uttam Kumaran: Yeah.
308 00:26:30.700 ⇒ 00:26:32.779 Zoran Selinger: A good reason behind it, yeah.
309 00:26:37.350 ⇒ 00:26:37.990 Uttam Kumaran: Okay.
310 00:26:40.750 ⇒ 00:26:44.910 Zoran Selinger: In terms of traffic, yeah, they do a lot. I see they do have…
311 00:26:45.380 ⇒ 00:27:03.259 Zoran Selinger: a lot of channels activated. And, I mean, Joe said so. He said there’s a lot of contractors working on different channels, and there’s a lot of stuff activated, and that’s very clear from GA.
312 00:27:06.190 ⇒ 00:27:10.890 Uttam Kumaran: Yeah, I think my… I think one piece to understand here also is,
313 00:27:11.220 ⇒ 00:27:21.819 Uttam Kumaran: I feel like the easiest place we can be helpful is on the conversion side, like, once they’re on the site. I am interested to know, though, if their traffic has changed over the last few years.
314 00:27:22.190 ⇒ 00:27:28.779 Uttam Kumaran: Because they don’t have… they don’t… they don’t do any sort of channel-by-channel ROAS, or…
315 00:27:29.250 ⇒ 00:27:37.550 Uttam Kumaran: segmentation. So, the interest… they’re gonna have interest in, like, how is traffic across various channels growing?
316 00:27:38.030 ⇒ 00:27:40.729 Uttam Kumaran: And how much of that is paid versus organic?
317 00:27:41.480 ⇒ 00:27:47.410 Uttam Kumaran: And then, on the paid side, right, what do we do? We go and look in, like, okay, how much are you spending? How much are you getting?
318 00:27:47.650 ⇒ 00:27:51.229 Uttam Kumaran: But even the high-level numbers, they just don’t have. So…
319 00:27:52.310 ⇒ 00:27:55.470 Zoran Selinger: Okay, that can be… I can… I can pull those.
320 00:27:55.690 ⇒ 00:27:57.829 Zoran Selinger: I can pull those.
321 00:27:58.670 ⇒ 00:28:02.259 Zoran Selinger: So, the data that you’re… that you’re looking at is…
322 00:28:03.170 ⇒ 00:28:10.540 Zoran Selinger: is one year, last year. So, basically the last 365 days.
323 00:28:10.540 ⇒ 00:28:15.260 Uttam Kumaran: I think that’s fine in terms of, like, the current state of conversion.
324 00:28:15.390 ⇒ 00:28:21.080 Uttam Kumaran: I think at the high level, we want to just look at, like, how did traffic change last 5 years or so?
325 00:28:21.290 ⇒ 00:28:24.570 Uttam Kumaran: Like, after 5 years, it’s really whatever, but…
326 00:28:24.930 ⇒ 00:28:34.830 Uttam Kumaran: sort of, that’s what we want to know, is like, is traffic still continuing to go up? How much of that are we paying for? Right? So generally, like, what is some of the high-level efficiency?
327 00:28:34.960 ⇒ 00:28:37.420 Uttam Kumaran: And then understanding
328 00:28:37.540 ⇒ 00:28:41.459 Uttam Kumaran: Okay, like, how much of that is going to… how much of that are we kind of, like, losing?
329 00:28:41.620 ⇒ 00:28:42.410 Uttam Kumaran: Right?
330 00:28:42.560 ⇒ 00:28:51.179 Uttam Kumaran: like, and I kind of want to… basically, when Clarence and I want to work on, like, what is the dollar value in lifting your conversion up 5%,
331 00:28:51.810 ⇒ 00:28:53.539 Uttam Kumaran: And my ask to you is, like.
332 00:28:53.780 ⇒ 00:29:04.720 Uttam Kumaran: what are the… what are the… what are the menu options that we will do, and do we think we can get them 5% conversion? What is that worth to them, and then how much do we cost to do that, right? That’s… that’s how we… that’s what we’re gonna do.
333 00:29:05.120 ⇒ 00:29:05.780 Zoran Selinger: Okay.
334 00:29:07.640 ⇒ 00:29:20.089 Clarence Stone: Yeah, and I’ll throw in that, like, we’re also trying to give better recommendations based on, like, the growth of certain markets, right, and the demand that they currently have. So, for example, Sauron, like, if
335 00:29:20.090 ⇒ 00:29:45.059 Clarence Stone: you know, I’m looking at, like, market-driven data saying, you know, pest control service is going to grow 9% as a CAGR in the next 5 years, but if they’re not capturing that full market, then, you know, we’d recommend, hey, invest in that, because it’s going to grow more, right? So, that’s why I was asking you about the service level segmentation. I got a little bit of that view from Amber already, so it helps, but it’d be really interesting to connect the two from the funnel into what the
336 00:29:45.060 ⇒ 00:29:46.280 Clarence Stone: are actually buying.
337 00:29:47.200 ⇒ 00:29:53.480 Zoran Selinger: Yeah, I’ll have… I’ll have to see if I have anything in… in terms of… in the events.
338 00:29:54.110 ⇒ 00:30:04.779 Zoran Selinger: I can gather a li- the only, the only service-specific data that I’ve seen is from queries from the Search Console.
339 00:30:06.130 ⇒ 00:30:10.760 Zoran Selinger: So that’s the only, only thing that I see at the moment in there.
340 00:30:10.760 ⇒ 00:30:16.969 Clarence Stone: I mean, if we don’t have that data, we don’t have it. It’s something that we have to tell them they need to work on and build out, so…
341 00:30:17.870 ⇒ 00:30:19.899 Zoran Selinger: I mean, yeah, I’m not sure if…
342 00:30:21.170 ⇒ 00:30:25.399 Zoran Selinger: if Google Analytics is the place.
343 00:30:25.720 ⇒ 00:30:29.709 Zoran Selinger: we would typically find that. I mean, we used to have…
344 00:30:30.670 ⇒ 00:30:33.660 Zoran Selinger: Few options for benchmarking in there.
345 00:30:34.210 ⇒ 00:30:39.720 Zoran Selinger: That was always very, very off with Google, honestly.
346 00:30:40.440 ⇒ 00:30:49.959 Zoran Selinger: And, I… slightly better things you can get from, just running, planning tools inside Google Ads.
347 00:30:51.330 ⇒ 00:31:02.200 Zoran Selinger: Anyway, so that’s… that’s maybe a better place where we can… when we can gather, like, potential number of impressions for each kind of service, and you can get
348 00:31:02.330 ⇒ 00:31:10.870 Zoran Selinger: pretty good estimates of impression shares, but from the… from Google Ads. This is not gonna live in… in Google Analytics.
349 00:31:11.280 ⇒ 00:31:12.550 Zoran Selinger: So, yeah.
350 00:31:12.740 ⇒ 00:31:24.449 Zoran Selinger: And we don’t necessarily need to have access to their account. We can use any Google Ads account to, to look at, you know, pest control numbers,
351 00:31:24.450 ⇒ 00:31:26.010 Uttam Kumaran: Oh, industry numbers.
352 00:31:26.540 ⇒ 00:31:42.639 Clarence Stone: Yeah, you know, I think it has also something to do with how they set up their tagging, right? Because, you know, when I worked at B&H, we would get SKUs for all the items that were in the, transaction, if there was a conversion.
353 00:31:42.890 ⇒ 00:31:45.609 Clarence Stone: So I could actually see, like, what items people actually…
354 00:31:45.610 ⇒ 00:31:47.520 Zoran Selinger: Oh, yeah, for sure, but the…
355 00:31:47.520 ⇒ 00:31:56.880 Clarence Stone: we’re trying to figure out what service did they buy, right? Because I don’t think that, like, the distribution’s gonna be equal. That’s what I’m interested in figuring out.
356 00:31:57.260 ⇒ 00:32:04.219 Zoran Selinger: Yeah, so we have very few transactions in a year here, okay? Very, very few.
357 00:32:04.520 ⇒ 00:32:07.990 Zoran Selinger: And that’s the… that’s the problem here. They have…
358 00:32:10.140 ⇒ 00:32:12.969 Zoran Selinger: It’s not really an e-commerce setup.
359 00:32:13.150 ⇒ 00:32:20.619 Zoran Selinger: in their Google Analytics. It’s not really an e-commerce setup. I don’t exactly know how their, is…
360 00:32:20.800 ⇒ 00:32:27.079 Zoran Selinger: I have to look at that video that… that Uta made of him going through the…
361 00:32:27.250 ⇒ 00:32:28.989 Zoran Selinger: Through the click to buy.
362 00:32:29.150 ⇒ 00:32:34.350 Zoran Selinger: I’m not even sure, I’ll have to look into that and see, is it even doable?
363 00:32:34.610 ⇒ 00:32:35.509 Zoran Selinger: In this case.
364 00:32:35.510 ⇒ 00:32:42.679 Uttam Kumaran: And I can go… I can go through that again if you want. I have more stuff I need in my house, so we can go through that again.
365 00:32:42.680 ⇒ 00:32:45.480 Zoran Selinger: I mean, if you have the video, I’ll look at the video.
366 00:32:45.480 ⇒ 00:32:52.320 Uttam Kumaran: I tried to be very, like, slow and, like, kind of click on all the options, so maybe you can, yeah, that’ll be helpful.
367 00:32:52.320 ⇒ 00:32:55.409 Zoran Selinger: So, that is a low-hanging fruit. If…
368 00:32:55.530 ⇒ 00:32:56.630 Uttam Kumaran: If we can…
369 00:32:56.950 ⇒ 00:32:58.480 Zoran Selinger: legitimately.
370 00:32:58.720 ⇒ 00:33:03.380 Zoran Selinger: Have a, like, a proper e-commerce, setup.
371 00:33:03.620 ⇒ 00:33:04.760 Zoran Selinger: for them.
372 00:33:05.720 ⇒ 00:33:16.160 Zoran Selinger: Obviously, that’s gonna be very valuable. That’s… that’s where the value of Google Analytics really comes into place, but it’s simply not
373 00:33:16.290 ⇒ 00:33:23.889 Zoran Selinger: not implemented here. We don’t have transaction IDs, we don’t have itemized transactions at all. I don’t… I don’t see anything.
374 00:33:24.060 ⇒ 00:33:24.979 Uttam Kumaran: Yeah, that’s horrible.
375 00:33:24.980 ⇒ 00:33:25.889 Zoran Selinger: We’re not set up.
376 00:33:26.400 ⇒ 00:33:27.619 Zoran Selinger: Simply not set up.
377 00:33:28.250 ⇒ 00:33:29.640 Uttam Kumaran: Yeah, that’s brutal.
378 00:33:32.200 ⇒ 00:33:35.079 Zoran Selinger: Yeah, I was, I was thinking maybe it’s…
379 00:33:35.330 ⇒ 00:33:39.840 Uttam Kumaran: Because you know why? Because I… because we have… I have all the enrichment data
380 00:33:40.000 ⇒ 00:33:47.120 Uttam Kumaran: On the people, you know, who’s buying the transaction in their… in their… in their CRM,
381 00:33:47.440 ⇒ 00:33:49.970 Uttam Kumaran: But, like, none of it can get sent back to GA.
382 00:33:53.590 ⇒ 00:34:00.160 Zoran Selinger: Yeah, yeah. So… That should be implemented. Did we… we…
383 00:34:00.630 ⇒ 00:34:02.780 Zoran Selinger: I don’t remember seeing an email.
384 00:34:02.900 ⇒ 00:34:06.389 Zoran Selinger: that we got the Google Tag Manager access, right?
385 00:34:06.500 ⇒ 00:34:07.030 Uttam Kumaran: Oh.
386 00:34:07.030 ⇒ 00:34:08.350 Zoran Selinger: No, but I’m here.
387 00:34:08.659 ⇒ 00:34:09.459 Uttam Kumaran: Let me do that.
388 00:34:09.460 ⇒ 00:34:10.709 Zoran Selinger: Seeing an email.
389 00:34:11.870 ⇒ 00:34:14.060 Zoran Selinger: Yeah, no invitations, yeah.
390 00:34:15.350 ⇒ 00:34:17.330 Zoran Selinger: I don’t see any invitations.
391 00:34:18.219 ⇒ 00:34:22.520 Zoran Selinger: So that would also be a… I mean, I’d be able to confirm
392 00:34:23.790 ⇒ 00:34:27.979 Zoran Selinger: whether they even attempted to implement the e-commerce tracking for GA.
393 00:34:31.489 ⇒ 00:34:35.699 Uttam Kumaran: Yeah, let me, let me do that, dude, that’s good.
394 00:34:36.379 ⇒ 00:34:38.069 Uttam Kumaran: What else? Do we need anything else?
395 00:34:46.520 ⇒ 00:34:53.020 Zoran Selinger: I mean, listen, if we can get access to any ad accounts, I mean, that would be valuable, obviously.
396 00:34:53.020 ⇒ 00:34:55.979 Uttam Kumaran: Okay, let me ask about Google Ads.
397 00:34:57.800 ⇒ 00:34:59.220 Uttam Kumaran: Facebook ads.
398 00:34:59.800 ⇒ 00:35:00.350 Zoran Selinger: Yup.
399 00:35:01.010 ⇒ 00:35:03.710 Zoran Selinger: Do we have access to Google My Business?
400 00:35:03.900 ⇒ 00:35:04.850 Zoran Selinger: Already?
401 00:35:10.460 ⇒ 00:35:12.890 Uttam Kumaran: I don’t have access…
402 00:35:14.020 ⇒ 00:35:20.009 Uttam Kumaran: I didn’t push on it, I can ask again. I just have, like, I have a list of all the Google My Business profiles.
403 00:35:21.000 ⇒ 00:35:24.170 Uttam Kumaran: So, let me just find that for you.
404 00:35:24.680 ⇒ 00:35:26.840 Uttam Kumaran: I mean, I don’t… yeah.
405 00:35:27.310 ⇒ 00:35:37.449 Zoran Selinger: I have query data in Google Analytics, so that’s something we can look into, from the Webmaster Tools, or what’s the name these days? Search Console.
406 00:35:37.720 ⇒ 00:35:38.560 Zoran Selinger: Yeah.
407 00:35:38.560 ⇒ 00:35:39.130 Uttam Kumaran: Yeah.
408 00:35:39.680 ⇒ 00:35:41.380 Zoran Selinger: So there’s this.
409 00:35:41.760 ⇒ 00:35:48.410 Uttam Kumaran: There’s… there’s this thing… departmental GBP Listing Tracker.
410 00:35:53.660 ⇒ 00:35:55.670 Uttam Kumaran: So I’ll make sure that you can…
411 00:35:58.990 ⇒ 00:36:00.130 Uttam Kumaran: See this…
412 00:36:02.760 ⇒ 00:36:04.639 Zoran Selinger: That’s some good stuff, okay.
413 00:36:05.640 ⇒ 00:36:07.370 Uttam Kumaran: And then,
414 00:36:10.530 ⇒ 00:36:15.450 Uttam Kumaran: That’s kind of all I have, actually, so… but you tell… but I never used…
415 00:36:15.920 ⇒ 00:36:23.950 Uttam Kumaran: I mean, I never… I’ve never done GBP analytics, so you tell me, like, I don’t know… How,
416 00:36:24.100 ⇒ 00:36:29.080 Uttam Kumaran: like, how would they give us access? Like, they give us ad… read-only access to, like.
417 00:36:29.200 ⇒ 00:36:31.970 Uttam Kumaran: And there’s a lot of them, so you just tell me, like, which ones…
418 00:36:32.660 ⇒ 00:36:34.580 Uttam Kumaran: you know, I just have to ask.
419 00:36:35.300 ⇒ 00:36:38.770 Zoran Selinger: Yeah, I haven’t done it either,
420 00:36:40.630 ⇒ 00:36:43.940 Zoran Selinger: So I’m not sure what we would see from it.
421 00:36:44.510 ⇒ 00:36:54.439 Zoran Selinger: But simply, just going by how important and how good it performs for them, we might be able to see something in there.
422 00:36:57.130 ⇒ 00:37:02.410 Uttam Kumaran: I mean, I would probably ask… I would… I could ask for just the biggest one, which is Austin Pest.
423 00:37:05.470 ⇒ 00:37:12.490 Zoran Selinger: It’s so annoying with queries from Search Console, because They do not…
424 00:37:13.350 ⇒ 00:37:23.939 Zoran Selinger: basically, that report is there in isolation on… of… of everything else in Google Analytics. So we cannot, for example, I cannot take,
425 00:37:24.590 ⇒ 00:37:29.910 Zoran Selinger: a search query, let’s say, ABC Pest… and…
426 00:37:30.860 ⇒ 00:37:44.180 Zoran Selinger: connected to conversions that we have in Google Analytics. It… you literally get… when you import it, you get 4 metrics, and they just sit in Google Analytics, isolated from everything else.
427 00:37:44.500 ⇒ 00:37:51.069 Zoran Selinger: So I only really have number of clicks, impressions, click rate, and the average position for each.
428 00:37:51.180 ⇒ 00:37:52.410 Zoran Selinger: each query.
429 00:37:52.640 ⇒ 00:38:02.149 Zoran Selinger: Oh, okay. Yeah, it’s very, very basic data. But we can… at least we can gather, Clarence, we can… we can get
430 00:38:02.640 ⇒ 00:38:09.230 Zoran Selinger: An idea of… of proportions, in demand for different services.
431 00:38:09.380 ⇒ 00:38:20.709 Zoran Selinger: We can get a sense of it, at least. Even if you don’t, for example, have access to Google Ads, we can get it from here, because we do have 42,000
432 00:38:21.050 ⇒ 00:38:29.650 Zoran Selinger: Search queries that are in… available to us, so we can mine that a little bit, and at least get those proportions.
433 00:38:29.980 ⇒ 00:38:34.810 Zoran Selinger: for particular… So each length, yeah.
434 00:38:36.570 ⇒ 00:38:43.499 Uttam Kumaran: Okay, so maybe I’ll send a follow-up in Slack, I have to jump to one more call, but I’ll send a follow-up. I do want to drive towards…
435 00:38:44.380 ⇒ 00:38:50.260 Uttam Kumaran: a couple of, like, sort of presentations here. So, probably something just around…
436 00:38:50.460 ⇒ 00:38:54.810 Uttam Kumaran: Traffic, and where the demand, and what does the demand look like?
437 00:38:55.220 ⇒ 00:38:57.830 Uttam Kumaran: Probably something around conversion.
438 00:38:59.280 ⇒ 00:39:00.150 Uttam Kumaran: Right?
439 00:39:00.300 ⇒ 00:39:03.679 Uttam Kumaran: and, like, more CRO, like, we could talk about that.
440 00:39:05.200 ⇒ 00:39:12.369 Uttam Kumaran: And they’re also, like, they’re gonna be interested in, like, AI SEO stuff, too. So I think that’s something that Ryan on our team
441 00:39:13.100 ⇒ 00:39:16.609 Uttam Kumaran: maybe him… he… him and you, Zoran, can pair.
442 00:39:17.130 ⇒ 00:39:24.690 Uttam Kumaran: So roughly, like, I think if we can layer in the AI SEO into the first presentation, then I think those two are really good.
443 00:39:25.190 ⇒ 00:39:25.860 Zoran Selinger: Okay.
444 00:39:26.720 ⇒ 00:39:27.270 Uttam Kumaran: Yeah.
445 00:39:27.750 ⇒ 00:39:30.880 Uttam Kumaran: Okay, I’ll, I’ll send some follow-ups in Slack, and this is great.
446 00:39:31.070 ⇒ 00:39:41.419 Uttam Kumaran: I think we’re on the right track, this is perfect. So I’ll also leave… I think I’ll follow up on, like, just next steps, and then Amber, I think we can all collaborate just on how to get this into, like, decks, some of these insights.
447 00:39:41.780 ⇒ 00:39:49.669 Uttam Kumaran: So the faster we can present a version of this, the more they’ll tell us the story, and then we can, like, chop off what not to focus on, basically.
448 00:39:50.090 ⇒ 00:39:51.210 Zoran Selinger: Okay, okay.
449 00:39:51.210 ⇒ 00:39:51.830 Uttam Kumaran: Okay.
450 00:39:52.860 ⇒ 00:39:53.870 Zoran Selinger: Let’s go. Okay.
451 00:39:54.350 ⇒ 00:39:56.390 Uttam Kumaran: Alright, thank you, dude, this was great.
452 00:39:57.820 ⇒ 00:39:58.460 Zoran Selinger: Okay.
453 00:39:58.460 ⇒ 00:39:59.810 Uttam Kumaran: Talk to y’all soon. Bye-bye.