2026-02-04_hold_brainforge_x_abc_final_presentation_8d5b44b0

Meeting Title: [HOLD] Brainforge x ABC: Final Presentation Date: 2026-02-04 Meeting participants: Uttam Kumaran, Amber Lin

---

WEBVTT

1 00:00:37.680 ⇒ 00:00:47.630 Uttam Kumaran: Let me get this to her. I’ll send her a big number. Okay, okay. Sorry. That’s my bad. I saw it go down, and then I didn’t think about it for a while.

2 00:00:48.590 ⇒ 00:00:54.250 Uttam Kumaran: I’ll send her this Zoom link.

3 00:01:00.230 ⇒ 00:01:06.939 Uttam Kumaran: And when you calculate your LTV, I mean, that’s… that’s an annual value.

4 00:01:08.720 ⇒ 00:01:13.729 Uttam Kumaran: What am I looking at? No, we are looking at the lifetime of the customer.

5 00:01:14.330 ⇒ 00:01:30.219 Uttam Kumaran: Now, again, these also include the initials, so if you’re a past customer, it would kind of count as 2. So this is the median LTV. This is the middle of the pack lifetime value of a customer, so the other way to think about it is, like, some customers on average, stay 2-3 years.

6 00:01:30.220 ⇒ 00:01:48.549 Uttam Kumaran: Right? And then, so there’s gonna be some that are… they never cancel, right? There’s gonna be some that cancel at the first, so we’re looking at right in the middle. I just wonder, yeah, what… if you could put together something that would better show the lifetime span of the customer. Yes. Right, what’s… how many… is 50% put within 3 years? Just go to 6 services there.

7 00:01:49.570 ⇒ 00:02:02.840 Uttam Kumaran: Right? Yeah. That’s… what’s that number? 2,800. If you have 6 services with ABC, you’re gonna spend over $2,800. Right. The problem is with this, the initial is counted in there as a service.

8 00:02:04.040 ⇒ 00:02:14.099 Uttam Kumaran: So, if you’re a pest customer, you… Yeah, what that seems to tell me is the customers aren’t… the lifetime span of a customer isn’t as long as I would have thought. I’m just telling you…

9 00:02:14.460 ⇒ 00:02:25.860 Uttam Kumaran: You go, go find me, go find me Mrs. Jones, who’s got 5 services, and I’ll tell you, she’ll have spent significantly more than $2,800 with us last year. Yeah, yes. That’s all I’m saying.

10 00:02:26.750 ⇒ 00:02:32.969 Uttam Kumaran: I’m just saying, Mrs. Jones is probably really the 10, because of how we’re counting some of these services.

11 00:02:33.080 ⇒ 00:02:42.530 Uttam Kumaran: I’m just saying. Mrs. Our lifetime value is unmatched for any service company, anywhere. Our potential. Yes.

12 00:02:43.850 ⇒ 00:02:55.229 Uttam Kumaran: Sometimes those not… might not be 6 repeats, but could be a one-time plumbing. A mosquito… I get all that.

13 00:02:55.410 ⇒ 00:02:59.640 Uttam Kumaran: That tree job was $2,000 in and of itself.

14 00:02:59.930 ⇒ 00:03:05.590 Uttam Kumaran: That plumbing job was $1,600. We’re both. We’re both right.

15 00:03:07.770 ⇒ 00:03:17.050 Uttam Kumaran: Yeah. That’s all I’m saying. Amber, I can pass to you for Dream.

16 00:03:18.750 ⇒ 00:03:21.240 Amber Lin: Cool, let’s do that.

17 00:03:21.240 ⇒ 00:03:22.240 Uttam Kumaran: Sorry.

18 00:03:22.240 ⇒ 00:03:24.480 Amber Lin: I’m glad I cr- I was…

19 00:03:24.480 ⇒ 00:03:28.679 Uttam Kumaran: He was sending me a message, like, your laptop’s dying, I was nodding.

20 00:03:29.750 ⇒ 00:03:32.610 Uttam Kumaran: Keep talking!

21 00:03:33.760 ⇒ 00:03:45.520 Amber Lin: Alright, so let’s go into dreams. So the first one I want to talk about is the lead funnel. We talked about it a little bit for Click to Buy, so the lead funnel is how

22 00:03:45.520 ⇒ 00:03:56.839 Amber Lin: we get a new lead, and then we prospect it, and then we assign it, I believe we assign it to a person, and then we go prospect them, and then we either go into

23 00:03:56.840 ⇒ 00:04:14.469 Amber Lin: they confirm, and it’s… we eventually sign a contract. So that’s the process, the general process of the lead funnel right here. And what I want to look at is, okay, how much of people… how successful is that funnel? And then,

24 00:04:14.560 ⇒ 00:04:16.600 Amber Lin: Where are people dropping off?

25 00:04:17.220 ⇒ 00:04:26.020 Amber Lin: So, let’s look at this. So, for the lease that we write down, so we… the lease that we put in our system, we…

26 00:04:26.020 ⇒ 00:04:39.549 Amber Lin: closed about 42% of them in 2025. Of course, this doesn’t account for the leases that we didn’t even get to put in our systems. So, for example, maybe on the people who left a website, or people who

27 00:04:39.550 ⇒ 00:04:46.340 Amber Lin: clicked on conflict buy, but then decided that, okay, I don’t want to finish this process, I don’t want to deal with it. So…

28 00:04:46.340 ⇒ 00:04:57.369 Amber Lin: But for the people that we did record down, we have about a 42% win rate. And then we also have 13%… Sorry, go ahead.

29 00:04:57.370 ⇒ 00:04:59.160 Uttam Kumaran: That’s lower than I thought.

30 00:04:59.380 ⇒ 00:05:18.190 Amber Lin: Well, part of it is still impending. So, in the pending, this is 17%, it’s contracts, I believe that’s… the customer said yes, but they haven’t finished signing a contract, they haven’t confirmed, so it’s still in the pending status. So overall, I would say you have.

31 00:05:18.190 ⇒ 00:05:20.110 Uttam Kumaran: 50…

32 00:05:20.220 ⇒ 00:05:29.720 Amber Lin: 55… 57-ish percentages, that’s in the completed status.

33 00:05:29.720 ⇒ 00:05:30.360 Uttam Kumaran: No.

34 00:05:30.470 ⇒ 00:05:40.990 Uttam Kumaran: the assigned is gonna be, like, a lot of your landscape guys that have a Dream account, but then they bid it on Dynascape, or HVAC. Where they have a Dream account, it’s pulling the data, but they’re not filling out agreements in Dream.

35 00:05:41.170 ⇒ 00:05:47.380 Uttam Kumaran: Yeah, good point. So, you basically just need to pull from sold, pending, loss, and void. Mmm, okay.

36 00:05:48.030 ⇒ 00:05:48.900 Amber Lin: Mmm.

37 00:05:48.900 ⇒ 00:05:51.480 Uttam Kumaran: We have users where it pulls that lead data.

38 00:05:51.600 ⇒ 00:05:57.880 Uttam Kumaran: But they’re not using Dream for all their agreements. Yeah, you wouldn’t get the quote out. I see. Victor Zombbeg, for example.

39 00:05:58.190 ⇒ 00:06:04.150 Uttam Kumaran: He only uses it for Tree. He uses Dynascape for all the other…

40 00:06:04.280 ⇒ 00:06:04.870 Amber Lin: Hmm.

41 00:06:04.870 ⇒ 00:06:11.140 Uttam Kumaran: all the landscape designers wanted to have a dream account, so we created them for them, but they hardly ever used it. What is the sign?

42 00:06:11.870 ⇒ 00:06:14.819 Uttam Kumaran: Just means it’s been assigned to a salesperson.

43 00:06:16.360 ⇒ 00:06:26.889 Uttam Kumaran: Yeah, I assume that… Amber, assigned is just assigned to… yeah, so what we should see is that those pieces close at the same close rate, and so it should end up being…

44 00:06:27.950 ⇒ 00:06:34.660 Uttam Kumaran: Should end up being higher. So, like, half of another 40%, so another 20%. Yeah.

45 00:06:35.480 ⇒ 00:06:37.150 Uttam Kumaran: Oh, okay.

46 00:06:37.360 ⇒ 00:06:55.090 Amber Lin: Yeah, and so here you also see that we were for sure 13% of them was either, voided or they were lost, and I’ll go into specifically what that means and what those reasons are in a bit, but this is a breakdown, so the next slide is a breakdown of,

47 00:06:55.090 ⇒ 00:06:59.060 Amber Lin: What the loss… what the drop-offs are.

48 00:06:59.080 ⇒ 00:07:09.070 Amber Lin: So, about, like, 70% of them are voided, so the customers, either said, I’d say…

49 00:07:09.900 ⇒ 00:07:11.230 Uttam Kumaran: So we never went out.

50 00:07:11.800 ⇒ 00:07:18.110 Amber Lin: Yeah, or they had, I believe, like, price issues. I have the list for those…

51 00:07:18.110 ⇒ 00:07:18.600 Uttam Kumaran: get a chance.

52 00:07:18.600 ⇒ 00:07:19.510 Amber Lin: Those are reasons?

53 00:07:19.510 ⇒ 00:07:43.630 Uttam Kumaran: Yeah. That’s the guideline for voice. Oh, never mind, I got someone else. Somebody else came out of here. These are of the losses. This is of the losses, yes. So, of the losses, what was the previous stage that they were in? So, complete pending, or they were open assigned. So, one of the key things when we look at sales opportunity analysis, or like, what you call deal velocity.

54 00:07:43.630 ⇒ 00:07:48.139 Uttam Kumaran: what I want to look at is, like, okay, what was the average age of

55 00:07:48.180 ⇒ 00:07:55.499 Uttam Kumaran: the ones that were in open, assigned, did they lose because they were just open too long? Yeah. Like, we didn’t move it along fast enough.

56 00:07:55.500 ⇒ 00:08:08.769 Uttam Kumaran: So it’s like, what is the actual learning as part of the fact that we realize? Second piece, yeah, that’s huge, that 8% of the ones, their previous status was complete pending. So what happened? Like, how did they get out?

57 00:08:08.960 ⇒ 00:08:14.000 Uttam Kumaran: at that point, right? And I don’t know, Amber, if you, if you…

58 00:08:14.000 ⇒ 00:08:29.170 Amber Lin: Yeah, that’s exactly what I went into in the next few slides. So, next slide, we can look at open assign. This is when the ticket gets opened, it gets assigned to a salesperson. So this is the very first stage we’re in touch with the… with the customer.

59 00:08:29.180 ⇒ 00:08:45.949 Amber Lin: And the reason why people drop off here at 20% is because the customer canceled the appointment. And I think that could have been that we didn’t confirm with the customer of what this service is. They might have been confused of what they were getting.

60 00:08:45.950 ⇒ 00:08:52.670 Amber Lin: Or, say, maybe we didn’t qualify the customers enough. So I think there’s a level of confusion there that…

61 00:08:52.670 ⇒ 00:08:59.629 Amber Lin: led to this high percentage of cancella… of just cancellations.

62 00:08:59.770 ⇒ 00:09:04.700 Amber Lin: I think that that’s something that we can also test with in our processes to see.

63 00:09:04.700 ⇒ 00:09:05.180 Uttam Kumaran: Yeah.

64 00:09:05.180 ⇒ 00:09:06.360 Amber Lin: will improve.

65 00:09:07.010 ⇒ 00:09:13.359 Uttam Kumaran: Oh, yeah, so, Amber, the suspicion is that the cancellation… the appointment was booked too far out, potentially.

66 00:09:14.120 ⇒ 00:09:18.440 Uttam Kumaran: We know that happens when we can’t call. We also…

67 00:09:18.610 ⇒ 00:09:25.640 Uttam Kumaran: This got put in at the end of the year, all last year. We didn’t send any type of confirmation once you called and scheduled a salesperson.

68 00:09:25.640 ⇒ 00:09:47.409 Uttam Kumaran: we never sent an email, we just verbally told them the date and hung up the phone. So I do wonder if we could look at… Now Evolve has it to where they get sent a reminder from Evolve. So that will be interesting to see how much that affects that number. So I do wonder, like, if we can look at how close to the appointment the cancellation happened. Yeah. But also, like, again, like, I assume… I know the CSRs.

69 00:09:47.410 ⇒ 00:10:02.309 Uttam Kumaran: there’s some mitigation around cancellations, but apart from that, is there anything else we’re doing to try to win back that customer after? Like, are we looking at all the people that canceled an appointment and saying, let’s put them into some campaign? Yeah, because this is bad on me. I’m shocked that number’s that high.

70 00:10:02.520 ⇒ 00:10:08.400 Uttam Kumaran: I mean, I believe… would think that once we’ve set an appointment.

71 00:10:08.450 ⇒ 00:10:16.240 Uttam Kumaran: to your point, I never thought we got that far booked out this entire year, because we were never that busy.

72 00:10:16.260 ⇒ 00:10:29.409 Uttam Kumaran: And so, I’d have thought that we were very responsive to when they called us. I mean, I get there were years before, we’re 2 weeks before anyone gets out there. Well, they set an appointment with us, they also set an appointment with 3 others.

73 00:10:29.530 ⇒ 00:10:37.450 Uttam Kumaran: first guy came, they bought from him, and, you know, the next two guys are SOL. But that was never the feeling in 2025.

74 00:10:37.450 ⇒ 00:10:53.849 Uttam Kumaran: we were very, I felt, very responsive on our time from set appointment, to call, to us being at their doorstep. Yeah. Hearing from that, just a lot of lost opportunities. Talking to the salespeople, that number does not surprise me.

75 00:10:53.990 ⇒ 00:10:55.950 Uttam Kumaran: Really?

76 00:10:56.770 ⇒ 00:11:04.310 Uttam Kumaran: Would you agree? Yeah, no, I know they claim there’s a lot of times it looks like I’ve got 5 on the schedule for the day, then I look at the end of the day, they end up with…

77 00:11:04.430 ⇒ 00:11:10.599 Uttam Kumaran: Let’s see, this is where I want to look at. I want to look at, was there something in this type of customer

78 00:11:10.600 ⇒ 00:11:33.119 Uttam Kumaran: That should… that could have indicated they were gonna cancel, right? Right. So maybe they’re coming from a channel that’s oftentimes, like, prickly customers. Maybe it’s that they went through Click to Buy and didn’t talk to someone, right? So those are the things where we start to back up, but right now, we don’t have great tie-ins between these systems, between Dream, Evolve, where they came from, and what they did on the site.

79 00:11:33.120 ⇒ 00:11:44.679 Uttam Kumaran: So one of the platform recommendations is gonna be to make sure you can tie in, because yes, for Amber to go all the way back and be like, okay, let’s look at just these. Where did they come from? Like, how did they actually get booked?

80 00:11:44.680 ⇒ 00:11:51.920 Uttam Kumaran: what service did they buy? We’re gonna continue to do the 80-20, and basically find… we’ll find the answer.

81 00:11:51.920 ⇒ 00:12:12.879 Uttam Kumaran: You know? So maybe it was a certain service that people always cancel. Okay, maybe there has to be some mitigation around that. Right, what’s the frequency? Or even if you look at it and say, alright, well, all these happen when we’re at least 4 days booked out, is when we see a flurry of these. Yeah, so maybe there has to be a text that goes out right at that moment when we know there’s gonna be high propensity to cancel.

82 00:12:13.290 ⇒ 00:12:21.960 Uttam Kumaran: That is the… so we’re, like… we’re one… we’re… right now, we’re two layers in, right? We looked at the overall, we then looked at…

83 00:12:21.960 ⇒ 00:12:39.090 Uttam Kumaran: just the cancels, access for 3 layers. Now we’re looking at, of the cancellation, so this is where we just peel the onion. We keep going, we keep going. Another thing I found is, I asked somebody one time, like, if a customer does move, say they… I can’t make it, for whatever reason, they just move it to a Sunday.

84 00:12:39.430 ⇒ 00:12:46.959 Uttam Kumaran: I don’t think anyone’s really following up. You know, I know… I think the sales guys are maybe supposed to, but they don’t have it at all. Why wouldn’t they move it to a Sunday?

85 00:12:47.250 ⇒ 00:12:51.969 Uttam Kumaran: No, no, but why wouldn’t you just move it to a…

86 00:12:52.470 ⇒ 00:13:10.609 Uttam Kumaran: I mean, yeah, I don’t know. They will say, I’ll call back and schedule. I would assume the office is trying to, and the customer says, I don’t know when. Customer says, I’ll call you. But again, if you don’t, if you… but again, a lot of… I know for me, like, I’m in meetings all day, I don’t pick up the phone at all during the day. And so, if you don’t have text.

87 00:13:10.810 ⇒ 00:13:31.550 Uttam Kumaran: rescheduling, or email-based rescheduling, so there’s just these other mitigation options that we have to explore. Yeah, that’s another layer of that onion, figuring out who these individuals are, because we might find interesting analytics on, you know, certain groups of people that may be more often than others, right? Like, maybe the first time people buy from you, if they run into scheduling issues, they…

88 00:13:31.550 ⇒ 00:13:35.900 Uttam Kumaran: they cancel more often. Like, that also tells us how we can, you know, target better.

89 00:13:40.430 ⇒ 00:13:40.980 Amber Lin: Awesome.

90 00:13:41.120 ⇒ 00:13:57.179 Amber Lin: I have a little bit more on the sources later, but this is just for when people drop off, when they already are at the complete pending stage. So this is when we’re almost so certain that they’re gonna stay with us, but still 8% of people still leave.

91 00:13:57.210 ⇒ 00:14:12.389 Amber Lin: And here, the main reason is because of price. Then, it makes me wonder of why, when they have almost completed, they should have known everything. Why is there still cancellations because of pricing issues?

92 00:14:12.390 ⇒ 00:14:24.859 Amber Lin: Is it because it wasn’t as transparent to them? Did they not know what would occur in terms of price? Do we qualify the customer correctly? Do we know,

93 00:14:25.170 ⇒ 00:14:36.999 Amber Lin: what they’re capable of paying before we invested all the time into, the sales process. So, I think this is also another area where we can see good improvements from.

94 00:14:37.260 ⇒ 00:14:46.149 Uttam Kumaran: I guess I’m… I mean, I’ve lost lots of business in my days because they thought the price was too high.

95 00:14:46.410 ⇒ 00:14:52.680 Uttam Kumaran: Well, I didn’t do a good job selling it, but at the end of the day, they went with somebody cheaper, is what it says.

96 00:14:52.750 ⇒ 00:15:09.730 Uttam Kumaran: And so, that’s just a normal… I don’t beat myself up for that one at all. Okay. Right? I mean, we’re going to… we are not going to be the cheapest. They are going to be able to get multiple providers to do it for less than we are, and…

97 00:15:10.220 ⇒ 00:15:26.359 Uttam Kumaran: particularly those entry-level customers are more likely to get multiple estimates. Sure. Right? I mean, for a termite estimate, the standard is always homeowners getting 3 bids. Well, we’re one of three.

98 00:15:26.360 ⇒ 00:15:32.869 Uttam Kumaran: I think it depends on the service. Sure. I don’t, again, it’s like what we said earlier, I don’t think people are getting multiple bits for pest control.

99 00:15:32.970 ⇒ 00:15:39.050 Uttam Kumaran: Right? Where it’s a $500 service. So, but, all I’m saying is…

100 00:15:39.100 ⇒ 00:16:03.849 Uttam Kumaran: I would expect to lose X number of them, because the price didn’t match the same thought. Or rodent, right? Well, they go, I wasn’t expecting to pay $1,200 on a rodent exclusion. So that’s the… one thing is for us to understand, are we… is this number okay? Right, so you said X number of them. So what is X, right? So we have to first consider, okay, like, what is our expected loss, and are we within a benchmark?

101 00:16:03.850 ⇒ 00:16:06.259 Uttam Kumaran: Well, let’s talk about that real quick. Sure.

102 00:16:06.260 ⇒ 00:16:13.369 Uttam Kumaran: So, it’s a scenario that we didn’t screw up. Yeah. Right? I got a guy on the doorstep.

103 00:16:13.370 ⇒ 00:16:20.590 Uttam Kumaran: when the customer said they wanted to see him. Yeah. Alright, so I have met my appointment, now I’ve got a

104 00:16:20.590 ⇒ 00:16:34.760 Uttam Kumaran: quality person on the doorstep, and he’s gonna do what he does, and he’s either gonna sell it, or he’s not. Yeah. Right? And most of the… most of the time that we don’t, it’s because

105 00:16:34.760 ⇒ 00:16:39.429 Uttam Kumaran: They’ve got someone who can do it cheaper. Yeah. Or the price was higher than they thought.

106 00:16:39.460 ⇒ 00:16:48.329 Uttam Kumaran: So, again, when I get a guy on the doorstep, my expectation is to close 70% of them.

107 00:16:49.040 ⇒ 00:16:50.010 Uttam Kumaran: Okay.

108 00:16:50.010 ⇒ 00:17:09.610 Uttam Kumaran: Right. Okay? Depends on the service, right? You can’t go into HVAC with that same hotel, right? 100%. Or water block. Right. But, for our bread and butter, I expect to sell 70% of those. Yes. So, of that 30%,

109 00:17:09.609 ⇒ 00:17:12.729 Uttam Kumaran: Again, it’s such a big difference.

110 00:17:13.079 ⇒ 00:17:35.270 Uttam Kumaran: For me, when I don’t get a guy on the doorstep, that’s the problem. Yeah, yeah, yeah. What happened there? Now I’m looking to point fingers somewhere. Where did we… did we not nail down the appointment? Did he not send the confirmation for the appointment? What happened that we thought we had an appointment? Did we not show up on time, right, ever? But when we put a guy on the doorstep.

111 00:17:35.880 ⇒ 00:17:42.460 Uttam Kumaran: My expectation is to close 70% of those, and the 30% that we don’t…

112 00:17:42.460 ⇒ 00:18:05.120 Uttam Kumaran: the vast majority of those are gonna be price. And I think Mark Johnson’s data backs it up to 70% by the time we get out there. What we pull on the sales guys, a lot of theirs on the residential, it takes out a lot of the voids. It’s basically just, of the services you were able to bid, once you’re there, we’re usually in that 65% to 70% range. But where I worry…

113 00:18:05.190 ⇒ 00:18:29.879 Uttam Kumaran: is these, what you were calling them, where we never even got out. Right, people that we paid to acquire, and then they… That’s my point. I paid to get somebody to call us, to do something, and we never even got to give them a proposal. That’s why we… That’s where I worried. That’s where I kept seeing that from the sales guys. I didn’t quantify it, but I just heard too many times where I’d see every day. Right, what you just said, I had 5, and only 3 are there.

114 00:18:29.880 ⇒ 00:18:45.790 Uttam Kumaran: What the hell is that? That’s why we went to Evolve and said, you guys have to do a confirmation reminder. I hope so. We’ll see how that helps. We’ll test it and see how much… So there’s gonna be a few of those that, again, it’s so easy to just get that set up, that we might as well have those.

115 00:18:45.830 ⇒ 00:18:55.969 Uttam Kumaran: Because I’m sure you’d be happy if that got to 80, and if it just took 3 text messages and email, right? So there are some things that it’s so… actually, we should just do the industry standard.

116 00:18:55.970 ⇒ 00:19:11.410 Uttam Kumaran: like, follow-ups and reminders, and then be okay with the benchmark. We’ve all seen the rise in the reminder for medical appointments. Oh my gosh, yeah. Because they… so that is one of… so that is one of the people makes you confirm a reservation, too.

117 00:19:11.410 ⇒ 00:19:25.550 Uttam Kumaran: So, medical and dental is where you’ll see, this is where private equity, they have it so modeled out that they… you’re seeing what is really so data-driven is what they do, and the systems they use, because we do… we have some clients in health.

118 00:19:25.550 ⇒ 00:19:48.289 Uttam Kumaran: It’s mostly around getting the person to the office for the service. Because they measured the cost of that lost appointment. Yes, and they’re like, they’re like, do anything to get them. But you can see what aggressive looks like, right? We won’t even tell them a menu of what we’re gonna talk about. Again, on the price one, I don’t worry about…

119 00:19:48.290 ⇒ 00:19:52.390 Uttam Kumaran: If it’s because we didn’t get it for price, as long as we’re closing.

120 00:19:52.390 ⇒ 00:20:02.289 Uttam Kumaran: At the appropriate percent. You know what I’m getting at. And one thing that Dream is now starting to do is, of the loss, there is a survey asking the customer, why did you pick us? That’s good business.

121 00:20:07.900 ⇒ 00:20:22.650 Amber Lin: Awesome. So next one is, we’re going to look at the sources. So this kind of overlaps with what we talked about earlier of existing customers, previous customers, customers who are coming from our lead line, from referral, and also

122 00:20:22.710 ⇒ 00:20:28.859 Amber Lin: the internet. So these are from different sources. Where are they coming from? How do they…

123 00:20:28.950 ⇒ 00:20:34.169 Amber Lin: How do they… how do our leads distribute between these sources? And…

124 00:20:34.310 ⇒ 00:20:50.949 Amber Lin: more than… more than half comes from either existing or previous customers. So this means that we have really good brand presence with them, they have a good impression of us, and they’re willing to call back us to say, hey, I want this new service, I want you guys to do it for us.

125 00:20:51.050 ⇒ 00:21:04.370 Amber Lin: But on the other hand, our, internet leads and creative leads are a lot less, so we don’t have a lot of net new customers that’s never been with us coming in.

126 00:21:04.370 ⇒ 00:21:11.070 Amber Lin: And I think that will be significantly improved by, say, more spending on advertising, optimizing.

127 00:21:11.070 ⇒ 00:21:24.030 Amber Lin: how we appear in organic search. So if, I think, if we’re able to improve that as well, we’ll see a significant increase in, the leads that we’re able to

128 00:21:24.400 ⇒ 00:21:26.109 Amber Lin: the opportunities I will have.

129 00:21:26.110 ⇒ 00:21:41.690 Uttam Kumaran: I gotta have a lot more understanding on that picture right there, because you’re blowing my mind. So this was… I was gonna say, are you guys… have you guys… are you familiar with the fact that it’s this breakout? No, no. And I’m beyond shocked.

130 00:21:41.880 ⇒ 00:21:49.109 Uttam Kumaran: I mean, I know we do a lot of business with existing customers. That’s great. And we’ve identified it.

131 00:21:49.220 ⇒ 00:21:55.940 Uttam Kumaran: biggest value proposition is to do more. Yeah. But I don’t understand where…

132 00:21:56.260 ⇒ 00:22:10.330 Uttam Kumaran: what’s… where’s our ad… is other the advertising? What’s… where is… where is… I saw you on TV, I heard your radio spot, I saw your billboard, I saw you online, where are all of those?

133 00:22:10.330 ⇒ 00:22:26.169 Amber Lin: Yeah, I can… I can give you a count. So, our people that come from the internet takes up about 6% of our leads. 6%-ish comes from sales auto, and then…

134 00:22:26.170 ⇒ 00:22:27.520 Uttam Kumaran: What’s so cool?

135 00:22:27.720 ⇒ 00:22:34.820 Amber Lin: I… I don’t really know. It’s what it’s called in the system, perhaps, is some automation campaigns that we send out.

136 00:22:35.960 ⇒ 00:22:44.989 Amber Lin: I believe Creative Lead is part of the, advertisement displays that we put up, so that’s where the creative leads are.

137 00:22:44.990 ⇒ 00:22:45.430 Uttam Kumaran: Can you stop?

138 00:22:45.960 ⇒ 00:22:56.379 Uttam Kumaran: customers telling the CSR… Yes. …what they put in is the new guests? Dream pulls this from Evolve. Yes. Right. So, the Evolve… this is the…

139 00:22:56.530 ⇒ 00:23:04.259 Uttam Kumaran: said, how’d you hear about this? Yes, right. Right, that’s where we don’t know, Joe. There’s…

140 00:23:04.840 ⇒ 00:23:22.529 Uttam Kumaran: when you create an account in Evolve, it’s what is the source when that customer was created, then when there’s a lead, when we create an estimate, there’s also a source there. So, I don’t… I really don’t know where Dream pulls from. Okay, we’ll find out. I would more so lean on Evolve.

141 00:23:22.560 ⇒ 00:23:31.510 Uttam Kumaran: on that. I’m just trying to understand… Yeah. …that I spent four to five million dollars on advertising.

142 00:23:31.580 ⇒ 00:23:33.530 Uttam Kumaran: And I’m wanting to know…

143 00:23:34.300 ⇒ 00:23:44.990 Uttam Kumaran: where does that show up on that pie chart? Yeah, so it’s gonna be a mix of other and creative lead, but that’s a good… that’s a good point, Amber. We should see from Julie

144 00:23:45.310 ⇒ 00:24:00.739 Uttam Kumaran: one, like, whether this matches Evolve, right? We know what I want is… we need to get… I want to know how many new customers… Again, it’s one thing that I sold something else to an existing customer.

145 00:24:00.740 ⇒ 00:24:23.450 Uttam Kumaran: That’s great. But I know we sold thousands and thousands and thousands and thousands of new people who’ve never done business with ABC, and they called us, and we sold them a service. So the question is, how did you hear about us? Yes. It had to be from… they weren’t a previous customer, they weren’t a this, they weren’t a that, it had to be… Used to be something.

146 00:24:23.450 ⇒ 00:24:34.359 Uttam Kumaran: Totally. I listen to KLBJAM, I hear, you know, we’d be asking what station we’re listening to. If you look at, as a percentage of revenue.

147 00:24:34.960 ⇒ 00:24:39.929 Uttam Kumaran: It’s gonna be smaller, and because, again, most of the people are buying one service.

148 00:24:39.930 ⇒ 00:25:03.610 Uttam Kumaran: And it’s typically not a high LTV service, unless you expand them. So as a percentage of total revenue, this is not the number of people, this is of the revenue generated. And yes, it’s… I think it’s still really exaggerated, but this… and this is from Dream. This is not including all your plumbing services, all your HVAC services, landscape. This is mostly your maintenance services. Through all this.

149 00:25:03.610 ⇒ 00:25:04.800 Uttam Kumaran: But I’d like…

150 00:25:04.910 ⇒ 00:25:21.359 Uttam Kumaran: We need to be… and this is what we should be counting. We talked about this a little bit earlier when we were talking about our percentage of advertising, but we’re doing it as a percentage of gross. Yes. We should be thinking it more in the percentage of terms of new service.

151 00:25:21.510 ⇒ 00:25:30.510 Uttam Kumaran: And that that generated these new calls. Yes. These new leads. These are new people, and all I’m saying is…

152 00:25:30.630 ⇒ 00:25:38.669 Uttam Kumaran: Yeah, it doesn’t do me any good to know this if I’m not calculating it against all new services. One times?

153 00:25:38.670 ⇒ 00:25:58.720 Uttam Kumaran: and new service agreements, right? What is that revenue that we generated? Because that’s what the advertising supposedly would have done. On the other hand, it’s also interesting, if there’s truly that much from existing customers, where did those come from? You know, because you’ve got, obviously, lead line, customer referral, I don’t know where, by the way, would be, but are those people…

154 00:25:58.750 ⇒ 00:26:08.430 Uttam Kumaran: Yeah, how are they… But how is it that big of a pie, and yet our average service is per customer is one point? But I wonder, Amber, if the existing customer’s all maintenance. Do you think this would match what we said we would

155 00:26:08.830 ⇒ 00:26:10.080 Uttam Kumaran: bought. Okay.

156 00:26:10.200 ⇒ 00:26:17.330 Uttam Kumaran: So the existing customer may just be people on maintenance, and that they’re just getting their services, right?

157 00:26:17.540 ⇒ 00:26:25.089 Amber Lin: Depends on what you guys would be logging in Dream, so… this is just Dream. It might be very skewed compared to Evolve.

158 00:26:25.090 ⇒ 00:26:36.280 Uttam Kumaran: But then that’s… If that’s in DREEN, it wouldn’t… that’d be the maintenance service that would be counted, though? No. Does it take…

159 00:26:36.310 ⇒ 00:26:50.010 Uttam Kumaran: the annualized amount. Yeah, when you sell something in Dream, it will take initial plus the maintenance. Right, for the first year. For the first year, and that’s what’s in the existing… That’s contract value of the first year. Right, yeah. Again, we’re not…

160 00:26:50.290 ⇒ 00:26:55.979 Uttam Kumaran: comparing apples to apples when we do it that way. We don’t have everybody on Dream. But who’s setting this up and creating the CSI?

161 00:26:56.160 ⇒ 00:27:06.299 Uttam Kumaran: So, Dream pulls, when a lead is created, or an estimate’s created in Evolve, that triggers to where it… The lead’s created by the CSR. Yes, what the CSR creates, then.

162 00:27:06.300 ⇒ 00:27:30.379 Uttam Kumaran: Dream automatically creates an opportunity. What I’m a little worried about is the CSRs clicking existing. Are they… yeah. They’re not asking, yeah. Because that’s up at the top. So I went through with Julie and looked through Evolve, and she actually has all of this set up, where you can pick the right sources. Yeah, and then I also wonder, Amber, we should… we should message the Evolve folks. We should message the Dream folks and see… Pull that number from

163 00:27:30.380 ⇒ 00:27:31.600 Uttam Kumaran: all-source scripts.

164 00:27:31.650 ⇒ 00:27:40.980 Uttam Kumaran: Yeah. Yeah, ultimately that’s what we do. Yeah. Yes. And then get ready to run.

165 00:27:40.980 ⇒ 00:27:48.490 Amber Lin: Cool. So if that number is not as accurate, let’s just skip the… skip to the next slide.

166 00:27:48.490 ⇒ 00:27:51.470 Uttam Kumaran: Checking cards. Go ahead. Go ahead, Amber.

167 00:27:51.940 ⇒ 00:27:53.389 Amber Lin: Yeah,

168 00:27:53.460 ⇒ 00:28:09.049 Amber Lin: Can we go to the next slide first? I just moved that around. So, I know, based on what we just said, the numbers are not too accurate, but, so disregard the ratios between the different sources, but I want to show you guys the…

169 00:28:09.050 ⇒ 00:28:19.590 Amber Lin: amount between the years, and I think we can see here that from 2022 to 2023, COVID years, things were really going well.

170 00:28:19.590 ⇒ 00:28:35.770 Amber Lin: But, say, for just 2024 to 2025, the internet leads, we are getting a lot less of people, of opportunities from the internet, and that matches what we showed earlier of the dip in…

171 00:28:35.770 ⇒ 00:28:49.439 Uttam Kumaran: The bottom part is actually, I think, more relevant than the top, like, all things are saying. We need to get the top accurate, that’s… No, no, no. Totally, totally. But I do think that the growth and the retraction rates…

172 00:28:49.710 ⇒ 00:28:56.530 Uttam Kumaran: Yeah. And I don’t know what a customer referral is, and I apologize, I’m not sure what that… is.

173 00:28:56.530 ⇒ 00:29:06.080 Amber Lin: That would be when someone, when asked, like, hey, how did you hear about us? They will say, someone that has a service with you recommended you guys.

174 00:29:06.080 ⇒ 00:29:17.190 Uttam Kumaran: Really? Yeah. And that’s where, yeah, I just don’t know, are the CSRs… is this… are they… we need to figure out where it came from, from Evolve, but then second, are the CSRs truly asking this, and…

175 00:29:17.190 ⇒ 00:29:35.270 Uttam Kumaran: documented correctly. So, one thing we can do, and we have the capability, we can go look at one of those deals and go all the way back to their transcript. That’s right. We should do a handful of those to see what we’re looking at. Those customer referrals, if those are accurate.

176 00:29:35.480 ⇒ 00:29:43.929 Uttam Kumaran: We’re getting those and doing nothing to promote that. And so the question is, well, what if we promoted that?

177 00:29:43.930 ⇒ 00:29:56.840 Uttam Kumaran: would that number be double? Clicky? Yeah, like, send us a customer, you get a free service, or you get… We have no… we have no customer… Yeah, I would definitely… I would take a handful out of every category and backtrack it, and let’s see how… Yeah.

178 00:29:56.950 ⇒ 00:29:58.829 Uttam Kumaran: Accurate. It is.

179 00:29:58.840 ⇒ 00:30:16.660 Uttam Kumaran: And those lead line numbers… But from what… when I… when talking to Julie, it seems like they’ve made a lot of progress in making this more accurate. So we spent… we spent a lot of time… because that was one of my… because without that data, especially for how much is done on the phone, we’re in a jam.

180 00:30:16.660 ⇒ 00:30:27.919 Uttam Kumaran: Which is… which is, again, why we should try to do more through click-to-buy, because then it’s… and… and that, because you… you can’t… it’s digitally tracked. But, from what I said, from what I saw, they’ve made a lot of strides.

181 00:30:27.920 ⇒ 00:30:34.969 Uttam Kumaran: So, I would… I think Julie would probably be the best person to show you how off this is, but I feel like this is…

182 00:30:35.370 ⇒ 00:30:40.350 Uttam Kumaran: they’ve done a lot better job in training the CSRs to input this, and have their… all the fields.

183 00:30:40.590 ⇒ 00:31:04.470 Uttam Kumaran: you know, I feel like a few years ago, we wouldn’t have been able to even have this. But although this is DREAM data, this is not evolved data. But from what we should assume, this is all pulling, yeah. Okay. Because no one… they’re not going into DREAM at all. Yeah, according to this, even, again, you would assume that, well, the numbers might not be accurate, the ratios you’d think would still be somewhat accurate, and you wouldn’

184 00:31:05.200 ⇒ 00:31:08.390 Uttam Kumaran: Yes. 16,000 in 2021, you’ve doubled your…

185 00:31:08.900 ⇒ 00:31:20.850 Uttam Kumaran: At the top, you doubled the number of existing customers, whereas everything else went down or flat? But you did grow your customer base during that time, right? So… I grew the revenue, for sure. Yeah. Okay.

186 00:31:23.150 ⇒ 00:31:26.199 Uttam Kumaran: Great, so I think a bunch of follow-ups there, for sure.

187 00:31:26.200 ⇒ 00:31:27.080 Amber Lin: Cool.

188 00:31:27.380 ⇒ 00:31:32.570 Amber Lin: So this is also an echo of, the…

189 00:31:33.460 ⇒ 00:31:42.349 Amber Lin: the… this is a percentage of how many people from that source is in each state. So…

190 00:31:42.400 ⇒ 00:31:59.579 Amber Lin: the more… the higher the percentage in the completed sold means more people from that source, got closed. So that’s a good thing. But the higher the number is in complete lost and void, that means we had a lot of drop-off.

191 00:31:59.580 ⇒ 00:32:09.080 Amber Lin: from people, from that channel. So, I think something I’ll point to is that for website and for click-to-buy,

192 00:32:09.180 ⇒ 00:32:24.470 Amber Lin: the drop-off rate is right here, one’s at 8.3, one’s at 9%. So, why are those, we’re having a lot of drop-offs from people coming from those, those sources.

193 00:32:24.740 ⇒ 00:32:41.330 Amber Lin: Which, like, those are the easiest sources we can adjust, and we’ll see the biggest effects from there. And then, of course, we can see that our existing and previous customers have the highest close rate, which is what we were expecting.

194 00:32:41.690 ⇒ 00:32:55.280 Uttam Kumaran: And even we, again, similarly, we may not see that as a problem. If these are the cheapest customers to get, and they just incrementally by 2%, then we actually may be okay, but you have to have that, like.

195 00:32:55.560 ⇒ 00:33:07.830 Uttam Kumaran: you have to know both sides to be able to see this and be like, okay, maybe it’s actually… and again, it’s all of an… it’s all an energy thing, it’s like, where do we put the energy to mitigating? This may not be…

196 00:33:07.840 ⇒ 00:33:18.640 Uttam Kumaran: such a big deal, right? If they’re only just 2 or 3% less, and we’re getting them for so much cheaper, and they don’t have to go talk to a CSR at all and spend that time.

197 00:33:18.640 ⇒ 00:33:29.919 Uttam Kumaran: And that it’s only resulting in 2% drop-off? That’s like, okay, that’s not great. Yeah. It’s not making my head explode. Yeah. So, on this chart, you do show TV, you got,

198 00:33:30.540 ⇒ 00:33:34.100 Uttam Kumaran: TV, television… TV twice, television and TV.

199 00:33:34.730 ⇒ 00:33:40.560 Amber Lin: And these are just the top… The bottom one should be a specific TV channel, based on what Dream is showing.

200 00:33:40.560 ⇒ 00:33:52.699 Uttam Kumaran: So sometimes people will say, like, I saw it on this channel, some people will just say, I saw you on TV. So, you can actually… basically, it gives them the path to be as accurate as the customer tells them. Yeah.

201 00:33:53.270 ⇒ 00:34:00.770 Uttam Kumaran: But, so, in data, like, these lead buckets, source buckets, and sort of bucketing people, it’s a huge…

202 00:34:00.860 ⇒ 00:34:19.829 Uttam Kumaran: thing that we do for a lot of people is customer segmentation on where they came from. But again, naturally, it should indicate to you, like, where and which you have issues in the purchasing process, which I think overall, again, as we… I think we’ve… compared to all the other parts that we’ve shown today.

203 00:34:19.830 ⇒ 00:34:29.459 Uttam Kumaran: We feel pretty good that, yes, there are probably some improvements that we make on a very automated basis to save some customers, but it’s not as bad, as…

204 00:34:29.460 ⇒ 00:34:47.990 Uttam Kumaran: if you’re thinking about total energy, just spend more time just acquiring the right customers and getting them into the funnel, right? So among those 3 buckets, I still feel like this is… this is important, but this is really just getting to the schedule. There’s still people that are getting to the schedule, doing the service, and canceling.

205 00:34:47.989 ⇒ 00:34:56.619 Uttam Kumaran: And that we’re not getting them back, and so that’s even another area of, like, retention and what we kind of call, like, resurrection. It’s basically what we call it often, you know?

206 00:34:59.870 ⇒ 00:35:00.790 Uttam Kumaran: Cool.

207 00:35:03.100 ⇒ 00:35:15.540 Amber Lin: This is my last slide, so this is just telling you, for our different… so for our top services, what are the sources they’re coming from?

208 00:35:16.280 ⇒ 00:35:35.500 Amber Lin: So, our signature pest control has the most people coming from different sources, so people are coming from internet, coming from leadline, television, so not just… this is the most discovered service, because not all of them are coming from

209 00:35:35.500 ⇒ 00:35:46.900 Amber Lin: existing customers. And in contrast, one time of skill suppression is almost 100% from existing customers. Of course, that is an add-on service.

210 00:35:46.900 ⇒ 00:35:51.369 Uttam Kumaran: Okay, that means we’re right. Okay, great. It’s an internal campaign.

211 00:35:51.370 ⇒ 00:36:04.160 Amber Lin: I see, I see. Makes sense. So, I think that also tells us of, okay, what service is… is it easier to get new customers from? So, we’ll use, say, Signature Pest Control as

212 00:36:04.160 ⇒ 00:36:21.650 Amber Lin: our marketing material, because people, are very receptive to that, versus something that people will have to think about, and they only trust you when they’re an existing customer that they’ve had experience with you. So that just informs when we adjust those emails, adjust those campaigns, what we will be able to do.

213 00:36:24.770 ⇒ 00:36:29.740 Amber Lin: Yeah, awesome. That’s all from me, and then I’ll pass it back to Utam.

214 00:36:29.860 ⇒ 00:36:32.490 Amber Lin: To talk about the other stuff.

215 00:36:32.490 ⇒ 00:36:39.550 Uttam Kumaran: Cool, the only slides that we didn’t go through, Amber, and I don’t know if… did we… did we talk about anything about cancellations?

216 00:36:39.550 ⇒ 00:36:42.929 Amber Lin: We… I can go through them really quickly, so…

217 00:36:42.930 ⇒ 00:36:46.600 Uttam Kumaran: I just want to show, like, the core cancellation…

218 00:36:47.200 ⇒ 00:36:56.230 Amber Lin: Yeah. Yeah. So this is a pie chart of what’s the most common cancellation reason, and people mostly cancel because.

219 00:36:56.230 ⇒ 00:36:57.630 Uttam Kumaran: Great conversation.

220 00:36:58.660 ⇒ 00:36:59.960 Uttam Kumaran: Sorry, sorry, go ahead, go ahead.

221 00:37:00.110 ⇒ 00:37:01.090 Uttam Kumaran: Oh.

222 00:37:01.090 ⇒ 00:37:18.159 Amber Lin: People mostly cancel because their contract is fulfilled, and they’re not renewing, or because they’re moving. As I was working with the CSRs, we were working on the safe tactics for the different reasons, and based on my observation, I don’t think there’s a

223 00:37:18.330 ⇒ 00:37:34.539 Amber Lin: clear renewal process of, okay, 60 days before their contract ends, call and say this. 30 days before, send them a discount, make sure they renew. Based on my observation, I think only mechanical has some sort of

224 00:37:34.540 ⇒ 00:37:47.629 Amber Lin: Procedure, but I don’t think it was readily enforced. So, if we were able to take that 30%, cut it by half by having them renewal, then that’s a lot of, lot of customers

225 00:37:47.690 ⇒ 00:37:50.219 Amber Lin: going out the door. So…

226 00:37:50.220 ⇒ 00:37:57.500 Uttam Kumaran: There was, a campaign at one time on the amps, the mechanical. Okay. That we would try and…

227 00:37:57.840 ⇒ 00:38:05.560 Uttam Kumaran: 60 days out, we would try and reinforce the value of it, those kind of things, but I don’t know how much they’re doing. Yeah, we should look into that and how the impact was.

228 00:38:05.770 ⇒ 00:38:24.960 Uttam Kumaran: There’s nothing that’s proactive on any of the other services, in terms that I’m aware of. We view them as evergreen. Right. Yes. So, once you have an evergreen contract, you go with it as long as… Assuming it’s gonna… Always. And obviously, we have a lot of customers who’ve been doing it forever. Yeah.

229 00:38:25.030 ⇒ 00:38:44.950 Uttam Kumaran: And, so when that contract fulfilled, that’s what those people, they’ve been with us for X amount of years, and, well, I just don’t need you anymore. Yeah. You don’t need us because you don’t have any bugs, and you don’t have any bugs because we do our job. Yeah. And we try and explain that. But do you have all these other…

230 00:38:45.010 ⇒ 00:38:47.940 Uttam Kumaran: You’re putting up lights, your trash smells, yeah.

231 00:38:48.280 ⇒ 00:38:50.899 Uttam Kumaran: Yeah. Is that a canceled? Yeah.

232 00:38:51.180 ⇒ 00:39:09.100 Uttam Kumaran: customer or canceled service? Well, and change service type. Okay, they went from one frequency to another. That’s not a cancellation. Yes. That’s just change, and again, we can… Usually the way all measures a cancellation is if a particular contract service is ended. Yes, yes.

233 00:39:09.100 ⇒ 00:39:11.619 Uttam Kumaran: We’re looking at the… yeah, exactly. So we’re looking at the…

234 00:39:11.620 ⇒ 00:39:15.249 Amber Lin: By service order, so this is the specific contract.

235 00:39:15.250 ⇒ 00:39:20.870 Uttam Kumaran: Yes, exactly. But I think this is where I… we… we spent some time talking about moving.

236 00:39:20.870 ⇒ 00:39:37.439 Uttam Kumaran: And we talked about interstate movements, and like, this is the pie for that. This is the opportunity for that, is really what, for me, everything else, I feel fairly comfortable that we have some hold on, and there’s more things we could do, but when we talk about campaigns around

237 00:39:37.440 ⇒ 00:39:41.860 Uttam Kumaran: moving, this is, like, this is the pitch to, like, do something about.

238 00:39:41.860 ⇒ 00:40:04.329 Uttam Kumaran: about that. How do we mitigate? So I think a lot of people even move within the same market. Most people, I mean, I don’t know, I feel like I don’t have the stats, but yes, most people are moving within the same market or the same state, like, you know, so there should be no reason, no significant reason why they can’t continue the Navy service. Additionally, when they’re moving, we talked about this, someone’s coming in.

239 00:40:04.980 ⇒ 00:40:23.340 Uttam Kumaran: So, couple points there. Yeah. I mean, so let’s do the moving one. Yes. So, alright, they’re moving. That’s not saying that we’re not… that we aren’t capturing them in their new home, but they still had to cancel that contract that they were in. That’s fair. So, it’s still gonna be…

240 00:40:23.470 ⇒ 00:40:30.059 Uttam Kumaran: canceled contract for moving. And then a new sale. And that’s fair. And then a new sale over here…

241 00:40:30.060 ⇒ 00:40:41.349 Uttam Kumaran: That, okay, and we did a good job on that, and I think we do okay with that. We should, we should look at the… Because the account is, is relative to the service address.

242 00:40:41.350 ⇒ 00:40:56.979 Uttam Kumaran: it would be a brand new account and a new service address, even if it’s the same customer. So we should look, Amber, on… after moving, how many people, basically, have a net new account with the same email. Now, obviously.

243 00:40:57.120 ⇒ 00:40:58.740 Uttam Kumaran: If they’re moving out of…

244 00:40:58.760 ⇒ 00:41:11.669 Uttam Kumaran: market where we don’t have one of our ABCs… We’re okay. But is… what we should find out is, are we in line with, basically, what the average people are moving to? Right. If X amount of people are moving out.

245 00:41:11.670 ⇒ 00:41:26.890 Uttam Kumaran: X percentage, are we kind of in line with that, right? Or are we close to that? So, I would like to see that as well. Similarly, though, I think this is the pitch for having a campaign that’s very targeted. Like, someone moving really is telling you that someone’s coming in.

246 00:41:26.890 ⇒ 00:41:34.439 Uttam Kumaran: So, that’s for sure. That is a net new… See, I think that of all of the… that I look up there.

247 00:41:34.740 ⇒ 00:41:47.919 Uttam Kumaran: that contract fulfilled. Okay. That’s the bucket that… Okay. They just weren’t wowed. Sure. They’re not happy. And if they really saw the value there, they wouldn’t… Right. We’ve allowed…

248 00:41:48.170 ⇒ 00:42:02.959 Uttam Kumaran: that number… that number is significant, and I bet a lot of those are ones like window. You know, window is one that they do it once, we put them… automatically put them on a maintenance, and then they say, well, I just want it once.

249 00:42:02.960 ⇒ 00:42:26.020 Uttam Kumaran: you know, I’d be curious how much does pest controls versus multiple? Yeah. I just think that there’s so few of those in comparison that it’s still not going to be a lot. I agree with you, that would be one that would be that, and okay, we’re doing better by trying… at least trying to get some on contract. The preponderance of those are maintenance pest control agreements that we’ve been doing for X number of years.

250 00:42:26.020 ⇒ 00:42:29.180 Uttam Kumaran: And what happens is, so my point is.

251 00:42:29.420 ⇒ 00:42:37.040 Uttam Kumaran: and I’ve written this down, you know, so is there an annual time to reach out? Yes.

252 00:42:37.040 ⇒ 00:42:53.979 Uttam Kumaran: And with an incentive, particularly in the first-year service agreement, right? So, before they get to the evergreen, right? Where they believe, I’m on a year contract, my contract’s up, now I’m canceling. Well, somewhere X months before that.

253 00:42:53.980 ⇒ 00:42:56.570 Uttam Kumaran: What are we doing to…

254 00:42:56.580 ⇒ 00:43:08.620 Uttam Kumaran: Right. Yeah. An incentive to stay, an incentive to, you know, do we give the customer a renewal contract, right? Should we have been doing that all along? Do we give them a reward?

255 00:43:08.620 ⇒ 00:43:22.989 Uttam Kumaran: Some type of, hey, you’re about to fulfill your year contract, we just bonus you some reward points. So, this is… That’s the thing. In our world, this is often called, like, churn prediction, and we… you basically have a good sense of

256 00:43:22.990 ⇒ 00:43:24.840 Uttam Kumaran: When and, and…

257 00:43:24.840 ⇒ 00:43:45.280 Uttam Kumaran: when and why, and what type of customer is going to churn, and then you build the campaign around mitigating that, right? You know, on average, X amount churn around 6 months after, especially for this service, maybe it’s faster. The email goes out to mitigate that. We tried to measure Raleigh and Houston was trying to say, well, if a customer has

258 00:43:45.390 ⇒ 00:44:09.140 Uttam Kumaran: more than one re-service, or more than two, then they were… okay, they’re a target to go after to say, alright, really… They’re likely to cancel, because they’ve already had some issues. Yeah. So the way, like, I mean, the way Amber… Amber and our strategy team do this is, these are called features, right? This combination of data, you have… these customers have all these features about them, you figure out what combination of features leads to what outcome.

259 00:44:09.240 ⇒ 00:44:19.659 Uttam Kumaran: this is the statistical analysis we just have to run. There is a… there will totally be an answer, but again, it’s the answer, then it’s like, okay, is there a marketing

260 00:44:19.670 ⇒ 00:44:36.999 Uttam Kumaran: way to mitigate that. Let’s just try sending an email out, running that for 3 months, coming back, looking at the customers that fit the building at 3 months, and do apples to apples. 3 months, same time last year, 3 months before. That is the round trip on that analysis, right?

261 00:44:37.000 ⇒ 00:44:47.489 Uttam Kumaran: And so, for us, commonly, when we work with teams, we’re putting together that one slide of this, and then we’re like, here is the recommendation. We should run this, we should have it run for 3 months.

262 00:44:47.490 ⇒ 00:45:01.789 Uttam Kumaran: then we should come back on this date and look and see whether we were right on mitigating that churn. Right. And then it’s just… Yeah. We’ve got a hard stop at 4.30. Okay, okay. Just cause we gotta get ready for our ownership thinking meetings at 5, and we’ve got to make sure the parking and…

263 00:45:01.830 ⇒ 00:45:06.199 Uttam Kumaran: Cool. Great. Thank you.

264 00:45:06.410 ⇒ 00:45:14.109 Uttam Kumaran: Okay, so I think this was sort of the last piece on, like, net new data. Yeah, what’s that? Okay, alright, we’re gonna explain this.

265 00:45:14.110 ⇒ 00:45:25.909 Amber Lin: I’ll do this real quick. This is what you guys were just talking about. This is per service. How long are they staying with us before they cancel?

266 00:45:25.910 ⇒ 00:45:26.600 Uttam Kumaran: Right.

267 00:45:26.600 ⇒ 00:45:44.809 Amber Lin: So you can look at… this is… sorry, this is a lot… we have a lot of services, so it’s… it’s very blurry, but just… I just want to point out two things that we want to look at. One at the top, one at the bottom. The bottom one is, pest control. So your… our most popular product.

268 00:45:44.830 ⇒ 00:45:51.429 Amber Lin: residential pest control every other month. People say about 2 years before they cancel.

269 00:45:51.440 ⇒ 00:46:06.729 Amber Lin: For termites, so on the top, termite inspection maintenance, people stay for almost about 4 years. So, these are just the different service and how long they stay with us, and yes, just as we discussed, this will go in

270 00:46:06.730 ⇒ 00:46:08.470 Amber Lin: To, when do we…

271 00:46:08.470 ⇒ 00:46:27.069 Amber Lin: message customers about, hey, you should renewal, you should think about this, here’s your reward, or how we should think about bundling things. If they’re using a service that usually lasts about one year, should we get them on another service that lasts longer, so they would

272 00:46:27.070 ⇒ 00:46:29.190 Amber Lin: So they wouldn’t be thinking about

273 00:46:29.460 ⇒ 00:46:38.790 Amber Lin: canceling as early. So, this is just another side of the data that we can pull, we can calculate to help inform better decisions.

274 00:46:40.040 ⇒ 00:46:41.570 Uttam Kumaran: Yeah. Wow.

275 00:46:42.600 ⇒ 00:46:44.110 Uttam Kumaran: That’s interesting.

276 00:46:44.110 ⇒ 00:46:44.760 Amber Lin: Yeah.

277 00:46:46.940 ⇒ 00:46:49.310 Amber Lin: Yeah, I know Utom had a lot of other stuff prepared, so…

278 00:46:49.310 ⇒ 00:46:50.449 Uttam Kumaran: No, I appreciate it.

279 00:46:50.450 ⇒ 00:46:50.920 Amber Lin: to go.

280 00:46:50.920 ⇒ 00:47:06.499 Uttam Kumaran: I’m super happy to keep sharing this. So, thank you, Amber, I appreciate it. Yeah, I mean, I want to spend the last 15 minutes sort of just talking about, like, what’s next. So, the first piece I want to talk about is, like.

281 00:47:06.580 ⇒ 00:47:20.160 Uttam Kumaran: what it took for us to even just pull all these together, and this is… for each of those sections, that’s probably 50% of what we went through directly with… with Steven and Bo. And so…

282 00:47:20.390 ⇒ 00:47:27.589 Uttam Kumaran: It took a lot of effort over the last two months, all kind of staggered, to push the entire machine to get the data in the right place.

283 00:47:27.590 ⇒ 00:47:42.770 Uttam Kumaran: And then we’re, like, very, very lucky to have folks like Amber, Zoran, Clarence on the team to kind of, like, whip these together. But I would say, like, it’s… it shouldn’t be this hard. And especially if we do this every day, all day, for a lot of people.

284 00:47:42.770 ⇒ 00:47:48.889 Uttam Kumaran: on… for the folks on your team to be able to do this, we really need to set the infrastructure up. And we’ve done some of those

285 00:47:48.890 ⇒ 00:48:04.080 Uttam Kumaran: plans already in putting this all together. And so, what I’m kind of showing you on the left is, like, really what the team size is. So, right now, internally, you have David and Brian. They’re really doing the 80-20 on just prep work, right? They’re using some Excel, some…

286 00:48:04.080 ⇒ 00:48:21.400 Uttam Kumaran: Power Automate, extremely manual, once a month, maybe just for one part of the business, right? And they’re running this all on their local laptops, so there’s nothing shared, and they’re not… they’re having to do the same work every month, instead of building on top of what they’ve already done.

287 00:48:21.400 ⇒ 00:48:35.770 Uttam Kumaran: And so right now, it’s not self-service, meaning you can’t… this crew can’t go somewhere and ask a question and get an answer back. Like, it has to be curated. A team like ours has to come in and sort of put this together. And there’s no redundancy, meaning

288 00:48:35.770 ⇒ 00:48:52.299 Uttam Kumaran: if David and Brian don’t show up to work, there’s a huge risk, right? And that kind of goes to my next piece, which is, like, just having a little bit of a bigger team is gonna allow you to actually have capacity for, like, proactive analysis, but even beyond the team size.

289 00:48:52.300 ⇒ 00:49:08.450 Uttam Kumaran: Being able to invest in, like, a modern reporting tool that’s gonna allow you to actually show this data and give access not only to this group, but other folks in the company. There’s some alternatives to Power BI that we commonly recommend. There’s also a data warehouse.

290 00:49:08.450 ⇒ 00:49:18.230 Uttam Kumaran: which is basically where we’re storing all this data. We actually have done this as part of our exercise, but this is, like, maintaining that and landing, continuing to land, dream, evolve.

291 00:49:18.230 ⇒ 00:49:35.750 Uttam Kumaran: Google Analytics data in one place. And then the last piece is, like, is creating these dashboards. So we don’t want to come in this meeting and continue to debate whether the data is accurate or whether we’re agreeing on the right metrics. We want to move past that and have something that, on a monthly basis, you can look at to see the health of the business.

292 00:49:35.750 ⇒ 00:49:47.819 Uttam Kumaran: to see each of those parts, acquisition, conversion, delivery, service, retention, right? And every month, we’re coming in and looking at, okay, what moved, what didn’t, what should we… what are the bets we’re taking?

293 00:49:48.030 ⇒ 00:49:54.769 Uttam Kumaran: You want to be able to have a meeting like this, like, basically, you want to be able to put this data together at any moment.

294 00:49:54.770 ⇒ 00:50:08.439 Uttam Kumaran: You know, it doesn’t just have to be 2 months of work to get all of this, right? And so that’s what we’re seeing from the companies that are really driving an efficient business and are growing effectively. This is what they bring us on to commonly do.

295 00:50:08.990 ⇒ 00:50:28.300 Uttam Kumaran: And so, like, that’s all on the, like, the data infrastructure side. And so, really, like, kind of, like, our… what I want to go into next is sort of, like, where we can support and, like, where we still think that there’s opportunity. And so, for us, there’s really two parts here. One is, there is fixed work in order to just continue to make sure you have insights.

296 00:50:28.300 ⇒ 00:50:31.399 Uttam Kumaran: That we can run business reviews like this.

297 00:50:31.400 ⇒ 00:50:47.920 Uttam Kumaran: That you actually have a feeling of, like, a control center to see all of your data, and that we’re able to enable the marketing executive that’s coming in with this, because I would be very surprised if that person,

298 00:50:48.130 ⇒ 00:51:02.050 Uttam Kumaran: knows that they’re walking the situation with, like, very, very little data. And that person’s job, if you’re hiring anyone, you know, worth their salt, is gonna use data to effectively drive their KPIs. And so.

299 00:51:02.160 ⇒ 00:51:18.680 Uttam Kumaran: this establishment of this data infrastructure for them is gonna be really, really important. So what all we’re talking about is, one, there’s a lot of things that need to get fixed in Google Analytics, in how we’re doing the attribution. We’ve walked some of that through last week on some of those fixes, but there’s

300 00:51:18.680 ⇒ 00:51:21.540 Uttam Kumaran: Just a common set of things we have to do.

301 00:51:21.540 ⇒ 00:51:46.480 Uttam Kumaran: There’s also this data and analytics accelerator, so this is just being able to take those revenue reports that we did, make them accessible, actually put them in a place where they update, and that you can, at any moment, basically pull up your laptop and see that information, not just on a monthly basis, like, at any time, you know? And a lot of the businesses we support, we end up giving them an SLA one day, where they can see the health of their business within the

302 00:51:46.480 ⇒ 00:51:54.009 Uttam Kumaran: day, right? So you’re not… no longer waiting a month or a quarter, or in marketing’s case, you’re doing things on a year-long basis.

303 00:51:54.250 ⇒ 00:52:12.200 Uttam Kumaran: like, you should be driving towards weekly, I want to see, how did we do last week? Like, what could we impact, right? And that’s what… that’s what we’re trying to enable. And then the last piece is just tooling and infrastructure, so making sure you have, like, a Power BI or an equivalent to do this reporting, that David and Brian have the right tools to use SQL to do their analysis.

304 00:52:12.280 ⇒ 00:52:22.249 Uttam Kumaran: And so, this is… this is… for this portion of work, it’s just fixed price for us to go do that. It’s… it’s… this is all we do every day for several clients.

305 00:52:22.470 ⇒ 00:52:24.980 Uttam Kumaran: So I’ll… I’ll leave this.

306 00:52:25.200 ⇒ 00:52:32.729 Uttam Kumaran: This really, this white piece is what we’re talking about, which is, like, this is private equity grade diligence work.

307 00:52:32.750 ⇒ 00:52:49.809 Uttam Kumaran: that we put together. It’s your ability to actually execute, see the data faster, see the blind spots, and actually go to the business and say, great, we need to run a campaign here. Not waiting 3 months, 6 months, a year to then look back and make these decisions. So, Utam, if we were to…

308 00:52:50.540 ⇒ 00:52:56.269 Uttam Kumaran: what we would probably likely have to do is to say, okay, here’s our total marketing spend. Yeah.

309 00:52:56.720 ⇒ 00:53:01.060 Uttam Kumaran: I’m gonna spend… this slice of it with you. Sure.

310 00:53:02.170 ⇒ 00:53:08.420 Uttam Kumaran: where would I re… you know, and again, that’s gonna tell us the rest of my buy’s gotta be more efficient. Yeah.

311 00:53:08.640 ⇒ 00:53:15.179 Uttam Kumaran: Okay, overall. So, I mean, that’s the analysis in total we’ve got to kind of look at. Yeah.

312 00:53:15.650 ⇒ 00:53:19.559 Uttam Kumaran: You know, for us to be able to spend $60,000 more, we’re gonna have to say, okay, well…

313 00:53:20.140 ⇒ 00:53:28.410 Uttam Kumaran: Our marketing budget per month is a lot more than that, so, okay, can we… can we say what portion of this do we slice off, and…

314 00:53:28.830 ⇒ 00:53:32.010 Uttam Kumaran: How do we get a better benefit overall? Yeah, and, and…

315 00:53:32.010 ⇒ 00:53:51.149 Uttam Kumaran: I wanna… I wanna even show you one more piece. This is just really for, like, getting the systems set up. Right, but this is… this is the, like, performance-based work. This is the setting up the recovery, the win-back campaigns, right? The people that canceled, the people that are about to cancel.

316 00:53:51.150 ⇒ 00:54:07.439 Uttam Kumaran: This is all the tagging, tracking, attribution, where did all the leads come from? And the last piece is… is on traffic. It’s all the SEO, it’s all the AI, and what we’ve tried to do here is, one, set up, like, what is our goal, and, like, what is the potential

317 00:54:07.600 ⇒ 00:54:27.529 Uttam Kumaran: money that we can actually bring back to the table, which is 80% of the leads, you should be able to see where they came from. Right now, it’s a small amount to be able to see where they actually came from. On the geo side, it’s, can we actually get you that increase back in organic traffic? And then the top is purely revenue recovery.

318 00:54:27.920 ⇒ 00:54:43.740 Uttam Kumaran: And so, like, the net-net, this is sort of… when I think about a lot of our work that we’ve done with ABC, we’ve always tried to come at it with an ROI focus and, like, a performance focus, meaning even since we did the Andy work, we’ve always tried to push

319 00:54:43.740 ⇒ 00:54:48.569 Uttam Kumaran: For, let’s win, show the growth, and then we’ll win together.

320 00:54:48.730 ⇒ 00:55:05.140 Uttam Kumaran: I will say this is not a common model in our business, but it is us showing that we’re gonna take on that risk to actually make sure that you hit those revenue targets, you’re actually able to bring that money in. So, for us, we’re seeing that, if you think about now, next, future.

321 00:55:05.460 ⇒ 00:55:15.799 Uttam Kumaran: We’re really confident that with these changes, and seeing how much the customers are worth, and our impact on bringing them to the table, what the potential revenue impact could look like.

322 00:55:15.800 ⇒ 00:55:26.660 Uttam Kumaran: And again, we’re talking about marketing dollars being worth 3X. I’m trying to share with you that it is… that the efficiency on those dollars you’re spending with us are gonna…

323 00:55:26.850 ⇒ 00:55:32.299 Uttam Kumaran: Are gonna trump that, and make every additional marketing dollar you’re spending more efficient.

324 00:55:32.470 ⇒ 00:55:40.240 Uttam Kumaran: Now, that’s the… that’s one of the keys, is can we make future marketing dollars we spend

325 00:55:40.520 ⇒ 00:55:42.290 Uttam Kumaran: More effective, more efficient.

326 00:55:42.480 ⇒ 00:55:52.920 Uttam Kumaran: So, yeah. And what kind of labor can you take away? Obviously, you got a new marketing director come in, so can they do this themselves? If no, then we have to get someone to do it. Yeah, what can you…

327 00:55:53.890 ⇒ 00:56:10.549 Uttam Kumaran: you gotta figure out how much were you gonna total spend on labor, and compare it out of what you would spend with y’all. Obviously, you’re basically viewing y’all as more labor, but it’s gotta come out of marketing, go to marketing budget. And what I want to share is, like, in marketing, and especially this category of performance marketing, this is how they price.

328 00:56:10.550 ⇒ 00:56:17.800 Uttam Kumaran: I would say rarely is there, like, does a data kind of company like ours also priced… usually it’s priced…

329 00:56:17.970 ⇒ 00:56:38.169 Uttam Kumaran: purely on labor, hourly rate, and so we’re… I want to make sure that we’re showing you that every dollar you’re spending, you’re gonna get 5 to 10 out in a multitude of ways, and that we want to drive that. And really, what’s shown… what’s given me the confidence to even put an opportunity like this on the table is what we saw in the data. Like.

330 00:56:38.170 ⇒ 00:56:41.690 Uttam Kumaran: The machine exists to be able to service much more business, and…

331 00:56:41.690 ⇒ 00:56:50.980 Uttam Kumaran: it’s clear that we can drive more organic traffic. Like, a 20… typical goals for a performance marketing firm would be, like, we’re gonna increase traffic by, like, 5%.

332 00:56:51.150 ⇒ 00:57:02.290 Uttam Kumaran: We’re really confident that we can get 20% more organic traffic in the door, convert that at a really high clip, and that’s just… that is no change on the back end.

333 00:57:02.370 ⇒ 00:57:09.879 Uttam Kumaran: Right? So that’s just business as usual and servicing that. That’s just all revenue in the door, and that’s just through changes in

334 00:57:09.880 ⇒ 00:57:22.710 Uttam Kumaran: conversion rate, like, the SEO, the GEO work, making sure that everything’s tagged, and this is really, like, this is all that our team does for a number of companies, so…

335 00:57:22.940 ⇒ 00:57:31.110 Uttam Kumaran: Yeah, we can, again, if Monkey Boy’s supposed to be doing this, what are we paying them for? Can we reduce that spend? You know, that kind of thing. Yeah.

336 00:57:32.210 ⇒ 00:57:32.880 Uttam Kumaran: Okay.

337 00:57:33.460 ⇒ 00:57:42.849 Uttam Kumaran: So I can… I can send this deck over and summarize this. I, I think, yeah, you tell me how… how best, what would work, and how to think about it.

338 00:57:43.110 ⇒ 00:57:48.590 Uttam Kumaran: But… I think, you know, Utom, we’re interviewing

339 00:57:49.170 ⇒ 00:57:53.590 Uttam Kumaran: 5 different people Monday. Sure. Right? So we don’t know what that looks like.

340 00:57:53.850 ⇒ 00:57:56.340 Uttam Kumaran: I don’t know, you know…

341 00:57:57.010 ⇒ 00:58:09.439 Uttam Kumaran: I’m real curious if I’d have had all 5 of them sitting here, one at a time, and hearing the presentation, but they’re, like, overwhelmed, or like, oh my god, that’s what I gotta have, or, you know, what is their… Yes.

342 00:58:09.550 ⇒ 00:58:28.199 Uttam Kumaran: take, right? Because I’m not sure Les’ take on this, I don’t know what it would have been. Sure. I don’t know. I mean, I really… I think it’s… I think you’re more than welcome, if you want us to talk to them, or if you want to give them this, no problem with that. I mean, I’m also incredibly interested in their feedback.

343 00:58:28.200 ⇒ 00:58:32.249 Uttam Kumaran: This is just from our experience in… in doing this.

344 00:58:32.300 ⇒ 00:58:42.720 Uttam Kumaran: Now, you know, 30, 40 times, and seeing this at companies that are, you know, in your ballpark and higher, and how they run an effective, you know, growth operation.

345 00:58:42.720 ⇒ 00:58:56.580 Uttam Kumaran: But I also… I also agree, like, that… that person is critical, that they’re on board with this, and that they also see the value. Definitely. Bring a brand new person in that doesn’t agree with that. And then it’s… it’s like, okay…

346 00:58:57.780 ⇒ 00:59:01.510 Uttam Kumaran: I’m outsourcing X things now.

347 00:59:01.950 ⇒ 00:59:11.950 Uttam Kumaran: And I’m looking at outsourcing X+. Yes. And then I’m looking at hiring plus… Yes. …and data, and…

348 00:59:11.950 ⇒ 00:59:22.170 Uttam Kumaran: I think most people would say, you only got really one and a half persons in your marketing department. Well, that seems pretty lean, because nothing that we talked about here today

349 00:59:22.170 ⇒ 00:59:39.100 Uttam Kumaran: is social media stuff, right? Or, you know, we talked about some of this stuff, but, you know, that’s not anything you would be doing, right? And that’s fine, but okay, that’s a gap in our overall strategy, I think we would agree.

350 00:59:39.120 ⇒ 00:59:57.119 Uttam Kumaran: how do I fill that gap, right? And one piece I want to highlight… one piece I want to highlight is, to do that strategy effectively, you’re going to need the attribution, you’re going to need the tracking, you need Facebook to be able to look at your website, understand where people are coming from, and optimize.

351 00:59:57.120 ⇒ 01:00:05.640 Uttam Kumaran: So, even in order to do that strategy, you have to do some of this foundational work. I will guarantee you that whoever does that is gonna tell you the same thing.

352 01:00:05.640 ⇒ 01:00:25.289 Uttam Kumaran: like, that’s… I think we even discussed this… It’s the same thing I was gonna mention to you. If you bring in talent that’s really great at making social media content, how would you know that it was working well without getting a system like this to be able to see those reports? So that’s why I think, you know, the fixed price solutions are really things that I think you need to have.

353 01:00:25.300 ⇒ 01:00:42.790 Uttam Kumaran: It will give you access to reporting and analytics and insights, regardless of, you know, who’s gonna run these analytics campaigns. Like, it’s not gonna be worth spending any of that money on campaigns until you can see very clearly, right? At any given day, you just go to that link and see how it’s going.

354 01:00:43.170 ⇒ 01:00:48.429 Uttam Kumaran: I think that’s table stakes, you know, to be able to see how your business is performing on a day-to-day basis.

355 01:00:51.230 ⇒ 01:00:52.320 Uttam Kumaran: Cool.

356 01:00:52.890 ⇒ 01:00:54.000 Uttam Kumaran: Good stuff.

357 01:00:54.250 ⇒ 01:01:05.229 Uttam Kumaran: My head’s exploded. Thanks for the time. Thank you. No, this has been… this has been awesome. I feel like we… it’s been really… of course, working with the ABC team is awesome. You know, just, Tom…

358 01:01:05.580 ⇒ 01:01:09.320 Uttam Kumaran: You know, we’re gonna do the question.

359 01:01:09.980 ⇒ 01:01:21.679 Uttam Kumaran: And let me just set this out real quick, your initial reaction, right, is that we’re in the markets we’re in, and we’ve got the services we’ve got.

360 01:01:22.190 ⇒ 01:01:28.899 Uttam Kumaran: I don’t see any substantive change to that. Yeah. So, high penetration in Austin.

361 01:01:29.180 ⇒ 01:01:37.730 Uttam Kumaran: low penetration in RGB, Waco, but all growth opportunities, right? And we’ve got a lot of services that are here today that could be there tomorrow.

362 01:01:37.870 ⇒ 01:01:42.999 Uttam Kumaran: My point is, we’re gonna do… $170 million this year.

363 01:01:43.300 ⇒ 01:01:45.299 Uttam Kumaran: So, that’s fine.

364 01:01:45.470 ⇒ 01:01:52.250 Uttam Kumaran: But how does this company, in the markets we’re in, with the services we’ve got.

365 01:01:52.440 ⇒ 01:01:54.840 Uttam Kumaran: Get to 500 million. Yeah.

366 01:01:56.030 ⇒ 01:01:58.740 Uttam Kumaran: That’s… that’s what I’ve gotta have.

367 01:01:59.890 ⇒ 01:02:01.730 Uttam Kumaran: a system…

368 01:02:01.890 ⇒ 01:02:14.049 Uttam Kumaran: a data that can drive it. I can go hire people, okay? I can… we can train people, we can deliver the services to achieve that.

369 01:02:14.170 ⇒ 01:02:18.150 Uttam Kumaran: But how does this piece of it…

370 01:02:18.340 ⇒ 01:02:35.399 Uttam Kumaran: The analytics and the marketing drive us to that level. I can go hire salespeople who can go sell it. Yeah. But the place that I’ve become less confident in in the last 3 or 4 years, whereas always before, I was very confident.

371 01:02:35.550 ⇒ 01:02:39.669 Uttam Kumaran: I was very confident, because this business, for…

372 01:02:39.940 ⇒ 01:02:47.729 Uttam Kumaran: 38 years, grew at an average of 12-15% a year, right? And we just kept chugging, chugging, chugging.

373 01:02:47.830 ⇒ 01:03:06.100 Uttam Kumaran: And now that’s not… and I get that’s harder to do the bigger the company, but we’ve got so much more stuff to do, that I’m like, well, it shouldn’t be a hindrance to us, but I’ve got to have systems in place that can help us

374 01:03:06.350 ⇒ 01:03:20.139 Uttam Kumaran: get to that end game, and that’s not the end game, that’s the next big place. Yes, a billion. So, so, so we… we have, we have several clients that we work with that are in the $100to$500 million range right now.

375 01:03:20.140 ⇒ 01:03:31.500 Uttam Kumaran: they are all investing in this to empower their teams to be able to operate and make these decisions, because out of all those things, the one thing you don’t have more of is time. You just now have 17…

376 01:03:31.500 ⇒ 01:03:33.180 Uttam Kumaran: things, right? And so…

377 01:03:33.180 ⇒ 01:03:56.740 Uttam Kumaran: part of it is being able to find the signal in all this noise. It’s being able to go to a meeting that we had in November, ask those questions, and get an answer that same day, so that you can turn around and say, guys, push this campaign out, right? A huge piece of it is people. But I think you have the people, right? I would tell you if, like, okay, there’s a huge pushback from even seeing any data or anything.

378 01:03:56.740 ⇒ 01:04:00.500 Uttam Kumaran: It’s all been… the reception has been really, really great. Everybody’s excited.

379 01:04:00.500 ⇒ 01:04:09.169 Uttam Kumaran: And I believe your ability to get the people, but there’s also process. Are we doing, like, business review meetings? Are people able to get the data?

380 01:04:09.250 ⇒ 01:04:16.260 Uttam Kumaran: act on that in a marketing fashion, or in a retention fashion? And can you start to enable more decisions?

381 01:04:16.330 ⇒ 01:04:29.899 Uttam Kumaran: Right? Instead of waiting on a quarterly or yearly basis, can more decisions happen weekly, and can they be, on average, more accurate for you to grow? And that’s what we’ve seen in our experience as the… as one of the key pillars of going from the 100

382 01:04:29.930 ⇒ 01:04:38.319 Uttam Kumaran: you know, to double, to triple that. And I don’t know, Clarence, have you had any experiences in seeing that as well? But that’s what… yeah.

383 01:04:38.790 ⇒ 01:05:00.359 Uttam Kumaran: Yeah, so I’ll just end with, I think there’s massive spending and centralizing data and providing insights, because I think in… especially within the last 3 or 4 years, the market hasn’t been very predictable, right? And it’s been very difficult to figure out what all is going on. Well, a lot of this, I go, is it us, or is it everybody? Yeah.

384 01:05:00.360 ⇒ 01:05:24.380 Uttam Kumaran: Yeah, and what’s really interesting about me is, like, just based on, like, how the data came out from Amber’s analysis, and what you were saying about using Pest as the leader in growing your business, like, it really shows that you had really great business instincts, and you still have them. Now you’re just looking for that data to reinforce it, because things are kind of, like, pattern-breaking, right? They’re not like they used to be. So, yeah, like.

385 01:05:24.380 ⇒ 01:05:42.969 Uttam Kumaran: as a response to this, like, the breakthrough to these higher levels is being more granular with your data, and getting to smaller bits of dials, and tuning those as you go. So it gets more and more specific, and you can’t really do that in your head in pattern match anymore. You do need systems and, you know, reporting platforms to see it.

386 01:05:44.250 ⇒ 01:05:58.120 Uttam Kumaran: Yeah, we all send that over, and then if you could get some more answers on the, what we’re talking about, the, the reasons for cancellations. Definitely. Yeah. Alright, well, we’ll… we’re gonna… our next step is to get someone higher. Yeah.

387 01:05:58.800 ⇒ 01:06:05.479 Uttam Kumaran: And if I can… if I can be helpful in that, please, like, let me know, yeah. It might be. I might send over a…

388 01:06:05.580 ⇒ 01:06:19.689 Uttam Kumaran: a resume, and this is the one that we like the most. You see these skill sets, probably on the computer tomorrow. We do that. Yeah. And then, alright, and then, back to analyzing this. Hey man, thank you. Good to see you, Steve. Drive carefully. Yeah.

389 01:06:19.710 ⇒ 01:06:35.970 Uttam Kumaran: I think your goals are totally achievable. I think we’re seeing that you’re getting… you have great organic presence, and we can just start to grow those through really easy methods. It’s very rare to have a company that has that much organic traffic.

390 01:06:36.030 ⇒ 01:06:50.230 Uttam Kumaran: most companies in this… in a lot of other sectors, are paying for every customer they get tons of money, like 30, 40, 50 bucks, right? So, I… there’s a clear path, and even in just optimizing the acquisition piece.

391 01:06:50.460 ⇒ 01:07:03.919 Uttam Kumaran: Once you nail that, though, it then goes into these tougher things, which is retention, and it’s this full funnel, which is sales see something, we see it in a meeting, we then get marketing to build a campaign around it, we measure the impact.

392 01:07:04.110 ⇒ 01:07:06.940 Uttam Kumaran: That takes a full team to do.

393 01:07:07.180 ⇒ 01:07:18.270 Uttam Kumaran: You know. Okay. Great stuff. Thank you. Appreciate it. Thank you all. Thank you, Amber. Bye, Amber. Thanks, Amber.