Meeting Title: Brainforge x ABC Home and Commercial: Weekly Project Check Date: 2025-09-04 Meeting participants: JanieceGarcia, read.ai meeting notes, Uttam Kumaran, YvetteRuiz, Samuel Roberts, Amber Lin
WEBVTT
1 00:01:29.320 ⇒ 00:01:30.460 YvetteRuiz: Hello!
2 00:01:33.120 ⇒ 00:01:33.960 Uttam Kumaran: Hello!
3 00:01:34.420 ⇒ 00:01:35.360 YvetteRuiz: Hi, Odam!
4 00:01:35.360 ⇒ 00:01:36.590 Uttam Kumaran: Yeah, I can’t know.
5 00:01:36.820 ⇒ 00:01:39.720 Uttam Kumaran: My video’s coming in and out. Give me one second.
6 00:01:40.670 ⇒ 00:01:43.340 YvetteRuiz: I know, I see a blurry, somebody.
7 00:02:08.850 ⇒ 00:02:09.820 Amber Lin: Hi there!
8 00:02:12.620 ⇒ 00:02:14.449 YvetteRuiz: Hi, Amber, how are you?
9 00:02:14.450 ⇒ 00:02:15.350 Amber Lin: Hi!
10 00:02:15.460 ⇒ 00:02:17.070 Amber Lin: Good to see you again.
11 00:02:17.600 ⇒ 00:02:20.049 YvetteRuiz: Yes, ma’am, good to see you.
12 00:02:20.500 ⇒ 00:02:24.980 Amber Lin: We have some really good progress this week. I’ll start sharing slides.
13 00:02:25.140 ⇒ 00:02:32.600 Amber Lin: And I think we’ll kick off with… This one.
14 00:02:38.800 ⇒ 00:02:39.820 Amber Lin: Okay.
15 00:02:40.070 ⇒ 00:02:43.810 Amber Lin: So, just wanna… are we waiting for.
16 00:02:43.810 ⇒ 00:02:47.040 YvetteRuiz: Oh, I’m sorry, Matt’s not gonna be here, and neither is Steven.
17 00:02:47.040 ⇒ 00:03:03.340 Amber Lin: Okay, awesome, so we’ll just get started then. I just want to kick off with, I know we demoed the new interface last week. We were working on a project plan, and we want to make a… see if we can make a decision on,
18 00:03:03.410 ⇒ 00:03:18.310 Amber Lin: a few things. I’ll let Sam present here, and then we also have an approximate hour estimate of how long this would take and when it would be available, so, Sam, feel free to take it, and then if you need to share a screen, let me know.
19 00:03:18.720 ⇒ 00:03:25.889 Samuel Roberts: Okay, yeah, no, I should be good with the slide up. But yeah, so essentially the idea is to, like, take Andy from just the…
20 00:03:26.280 ⇒ 00:03:38.889 Samuel Roberts: the Google Chat interface, bring it into a more customizable chat interface that we can do, that we can connect with that, contextual AI, the demo that I showed, last time or the time before.
21 00:03:39.160 ⇒ 00:03:42.949 Samuel Roberts: With that, as we’re working on bringing the,
22 00:03:43.250 ⇒ 00:03:56.360 Samuel Roberts: the 8x8 transcripts in, we’ll be able to, you know, in addition to what Andy can already do and already knows, we’ll also know that. So, theoretically, we could do that in the Google Chat, but we won’t be able to surface
23 00:03:56.510 ⇒ 00:03:59.500 Samuel Roberts: documents or parts of the transcript, it would just be…
24 00:03:59.610 ⇒ 00:04:09.389 Samuel Roberts: information in the chat, which is a great interface for a lot of things, but being able to surface things next to it, talk over that, have it surface things as things are happening.
25 00:04:09.470 ⇒ 00:04:22.229 Samuel Roberts: This custom UI would allow us to show more of that, and then be able to add more things moving forward. As you can imagine, like, the Google Chat is just text back and forth. Right.
26 00:04:22.380 ⇒ 00:04:37.010 Samuel Roberts: So, this is essentially the idea is to… yeah, we have to re-architect a little bit of how Andy communicates, because obviously it’s going into Google now, and it would be going into a different UI. It’s a pretty nice UI, I think I showed that in another one.
27 00:04:37.680 ⇒ 00:04:55.340 Samuel Roberts: But, essentially, like, using a few different technologies, the Copilot Kit, which is the nice UI that is very customizable, we can skin it different ways and do different things. The contextual demo we did last time that surfaced those documents would hopefully be able to talk to the transcripts and see all the historical stuff. We’re still trying to figure out
28 00:04:55.390 ⇒ 00:05:04.039 Samuel Roberts: kind of potential for live things. And then there’s other kind of orchestration tools that’ll allow it to potentially more easily plug in
29 00:05:04.120 ⇒ 00:05:22.289 Samuel Roberts: tools or agents, that would allow this to scale to other things. So as we add more, as we add more features moving down, spread it out to other things, this would allow it… this kind of framework, this co-pilot kit framework that we’re gonna be using, would allow it to more easily say, like, okay.
30 00:05:22.400 ⇒ 00:05:30.689 Samuel Roberts: Andy, you now know about this other tool, you now know about this other data, you now know about this other thing, and so it kind of allows it to scale
31 00:05:31.230 ⇒ 00:05:37.150 Samuel Roberts: More easily stuff on the back end, but also for what we can do on the front end to visualize things and display things.
32 00:05:37.600 ⇒ 00:05:43.729 Uttam Kumaran: Yeah, a couple of features that we were talking about, Sam, were even things like, if you want to see conversation history.
33 00:05:43.730 ⇒ 00:06:06.760 Uttam Kumaran: If you wanted to search across all 8x8 transcripts, right, there were a couple of, like, helpful features that I think we could provide. Additionally, pulling in information directly from the CRM, like, when you, when you… when a client calls in, you can bring in the information just about them and start to have a dedicated chat interface just about
34 00:06:06.760 ⇒ 00:06:31.509 Uttam Kumaran: their information, seeing past historical information about them. So part of this is, like, I don’t… what I told… talked to Sam is I don’t want to replicate 8x8. Like, this needs to be something that is, like, distinct and different, but also, we’ll pull data from 8x8, we’ll pull data that we have already in ANDI, replicate the same features, but add additional things, like having a conversation history, so you can see past conversations with Andy.
35 00:06:31.510 ⇒ 00:06:39.389 Uttam Kumaran: seeing past transcripts in one place, searching over transcripts. So those are all things that we’re considering, you know, for something that’s more of a dedicated
36 00:06:39.480 ⇒ 00:06:44.329 Uttam Kumaran: you know, UI, for this project. Okay.
37 00:06:44.330 ⇒ 00:06:56.229 YvetteRuiz: Okay, and just so you guys know, I… you saw the chat, so I was… I met with Abe just right now before I met with you guys, and the reason I met with them… we were supposed to meet next week, but I just found out that…
38 00:06:56.690 ⇒ 00:06:59.450 YvetteRuiz: Our rep, he’s leaving, and today was his last day.
39 00:06:59.450 ⇒ 00:07:00.080 Uttam Kumaran: That’s, like.
40 00:07:00.080 ⇒ 00:07:00.820 YvetteRuiz: That’s.
41 00:07:01.130 ⇒ 00:07:02.640 Samuel Roberts: Oh, okay.
42 00:07:02.640 ⇒ 00:07:22.510 YvetteRuiz: he caught that meeting with me to introduce me to the new person, but anyhow, we did have the conversation. They’re gonna, get their, engineer, and then we’re gonna see… I told him the sooner the better that we can all connect, you guys can connect with them, so I’m hoping next week, so if you guys can share with me y’all’s availability, so then that way you guys can connect.
43 00:07:23.020 ⇒ 00:07:23.940 Uttam Kumaran: Okay, perfect.
44 00:07:24.300 ⇒ 00:07:31.290 Uttam Kumaran: Alright, and then, yeah, probably on this project plan, I think the one thing, Yvette, is I just need to… we sort of scoped out
45 00:07:31.530 ⇒ 00:07:45.930 Uttam Kumaran: what, like, executing on this would look like. Right now, we didn’t sort of budget for this in our kind of existing scope, so I want to have a conversation with Matt, and sort of get a sense from him on, like, hey, this is how many hours on our side it would take to develop.
46 00:07:45.960 ⇒ 00:08:02.629 Uttam Kumaran: There is probably gonna be, like, an additional fee that we need. Okay. But I’ll talk to him and see, like, what he’s in for. Main things, I just wanted to just confirm that, like, this is something that… that certainly I think you’re interested in, and something that I think would give us
47 00:08:02.630 ⇒ 00:08:07.269 Uttam Kumaran: a couple of more use cases for making sure Andy is adopted, but also
48 00:08:07.300 ⇒ 00:08:14.879 Uttam Kumaran: we can only go so far in using just the Google Chat, so I want to make sure that we’re… we can start to develop more
49 00:08:14.880 ⇒ 00:08:28.650 Uttam Kumaran: features that can get used by not only CSRs, but the trainers, and add things that even we would like to do, which is, like, chatting over transcripts, getting feedback for people, some more things like that. So that’s probably, like.
50 00:08:28.650 ⇒ 00:08:36.410 Uttam Kumaran: kind of where we’re at right now, so if you’re okay, I can put this plan in front of Matt and sort of get his feedback on, like, what budget would look like.
51 00:08:36.419 ⇒ 00:08:49.519 YvetteRuiz: Yeah, if you want to start working on that, that’ll be great and stuff, because, I mean, I know that, you know, the goal is eventually to start using it at a higher scale as well, you know what I mean? I know you’re starting off with us and stuff like that, so yeah, for sure.
52 00:08:50.230 ⇒ 00:08:51.800 Uttam Kumaran: Okay, perfect.
53 00:08:51.980 ⇒ 00:08:52.650 Samuel Roberts: Great.
54 00:08:52.650 ⇒ 00:08:54.180 Uttam Kumaran: Excellent.
55 00:08:57.180 ⇒ 00:08:58.880 Uttam Kumaran: Okay.
56 00:08:58.990 ⇒ 00:09:05.519 Amber Lin: Sounds good. And I think at the meeting, we’ll try to find a vacancy for next week, so we can get that booked.
57 00:09:08.390 ⇒ 00:09:25.619 Amber Lin: So, going back to our usual usage tracker, so, last week, we saw that usage weren’t as high, and then this week, it was a shorter week. So, I think, reasonably, the usage would be a little bit lower than the previous one. I’m hoping for
58 00:09:25.620 ⇒ 00:09:28.489 Amber Lin: Next week, we’ll see it climb up again.
59 00:09:29.880 ⇒ 00:09:40.279 Amber Lin: I did check to compare the previous… this and previous weeks, and, for the same time period, so Tuesday to today,
60 00:09:40.790 ⇒ 00:09:47.049 Amber Lin: our usage actually 70… I think 75% higher than the… than last week.
61 00:09:47.270 ⇒ 00:09:49.990 Amber Lin: So we have…
62 00:09:50.130 ⇒ 00:10:02.849 Amber Lin: I do… I am pretty confident about the usage going up, so we’ll see next week how it is. I looked… also, I looked at the usage, and I digged in a little bit more on the KPI side.
63 00:10:03.190 ⇒ 00:10:19.809 Amber Lin: So, here on the top, you can see Rosalinda’s at the top, and then following is Brian. So I went ahead and looked at Rosalinda, because I know she’s new, but she’s taking calls already now, so I want to… I wanted to ask you guys,
64 00:10:20.580 ⇒ 00:10:26.879 Amber Lin: so I checked on her calls. So, she is taking quite a lot of calls,
65 00:10:27.260 ⇒ 00:10:35.810 Amber Lin: even if… even though she’s new, so she’s up on the list, along with, say, Martha, April, Denise, so she’s
66 00:10:36.400 ⇒ 00:10:40.920 Amber Lin: She’s taking a lot of calls, and she has the most number of…
67 00:10:41.200 ⇒ 00:10:49.249 Amber Lin: Andy Assisted calls. So, I wanted to ask you guys of what type of,
68 00:10:49.590 ⇒ 00:11:01.439 Amber Lin: metrics can you look at to measure, is her calls as effective? Because I was checking her average handle time. Her average handle time is around, 6.1.
69 00:11:02.200 ⇒ 00:11:20.890 Amber Lin: minutes, and, it’s still higher than the other folks, but based on the fact that she’s taking that many calls, I think there’s something that’s working here, and I want to see… check with the guys, what can we measure there? What can we look at there? Should we listen to some of her calls?
70 00:11:21.790 ⇒ 00:11:31.359 YvetteRuiz: That’s where I was hoping, like, transcripts would really, really help us, in… in… in this, you know what I mean? To be able to connect…
71 00:11:31.840 ⇒ 00:11:33.340 YvetteRuiz: And, and see…
72 00:11:34.250 ⇒ 00:11:45.690 YvetteRuiz: what those conversations are, you know, what it is that she’s… what kind of conversations she’s having with the customers. She’s actually one that we talked about, because we were looking at…
73 00:11:46.210 ⇒ 00:11:49.149 YvetteRuiz: One of the things that we noticed with the pest division.
74 00:11:49.540 ⇒ 00:11:58.659 YvetteRuiz: and we just had this conversation with Shannon last week, is we have agents that vary. So, Uda might mention this, as well.
75 00:11:59.280 ⇒ 00:12:11.329 YvetteRuiz: we’re missing our service level, and our agents are kind of all over the map, right? You have high performers that are taking anywhere between 70 to 80 phone calls, and you have some… a lot, that are still in the
76 00:12:11.670 ⇒ 00:12:18.869 YvetteRuiz: Not going past 50 phone calls. And when you have that big of a difference, we’re trying to really dive in to see, okay.
77 00:12:19.410 ⇒ 00:12:30.180 YvetteRuiz: what kind of calls are they getting, and how can we get them to start taking more phone calls? What are they struggling with, what type of phone calls, and then how are they using Andy?
78 00:12:31.950 ⇒ 00:12:39.180 YvetteRuiz: But trying to pull those phone calls and figure out what exactly… what type of the… what type of calls those are.
79 00:12:39.910 ⇒ 00:12:47.730 YvetteRuiz: is I… I would… I would think you would have to start pulling more… going into… pulling more phone calls, and then using the transcripts. That’s just my… my thought.
80 00:12:47.730 ⇒ 00:13:01.139 Amber Lin: Yeah, that’s what I wanted to do earlier. I was working on a KPI dashboard, and I tried to… I wanted to compare, okay, how does, say, Rosalinda and Amy Richards
81 00:13:01.300 ⇒ 00:13:11.289 Amber Lin: average handling time compare. And then I realized that when they use ANDI, it’s for the questions that they don’t know, so naturally those calls would take longer.
82 00:13:11.290 ⇒ 00:13:11.770 YvetteRuiz: congrats.
83 00:13:11.770 ⇒ 00:13:15.620 Amber Lin: So, a reasonable comparison is, okay, for cancellations.
84 00:13:15.700 ⇒ 00:13:33.570 Amber Lin: how does the average time of people who don’t use Andy, who… or who use ANDI, how does those two groups compare? Before that, we’re going to need the transcripts. I can only see so much from the questions they ask Andy. So that’s something that we’re working on right now.
85 00:13:34.080 ⇒ 00:13:34.690 YvetteRuiz: Yep.
86 00:13:35.130 ⇒ 00:13:35.710 Amber Lin: Yeah.
87 00:13:36.040 ⇒ 00:13:54.950 Amber Lin: Next one is the lead line, because this is… I couldn’t see this, and I wanted to ask you guys, because we don’t have the lead line folks’ KPIs, because they don’t take calls. So is there a way you guys can measure the lead line folks’ KPIs? Is it how many sessions they schedule per week?
88 00:13:55.240 ⇒ 00:13:58.060 Amber Lin: How does that work for the lead line team?
89 00:14:00.150 ⇒ 00:14:09.620 YvetteRuiz: The lead line team does not report under me. They nor… they use… I don’t even know how they track any KPIs. I’d have to find out from…
90 00:14:09.620 ⇒ 00:14:14.049 YvetteRuiz: Whoever they report to. The reason they’re utilizing this is because they…
91 00:14:14.050 ⇒ 00:14:30.300 YvetteRuiz: the majority of the… what they use Andy for is the inspector’s zip code. That’s what they do. They’re, they get the web request… well, now we get them, but, they get any requests that come through the web, or any leads that go to them. And quite honestly.
92 00:14:30.690 ⇒ 00:14:36.120 YvetteRuiz: Now that I’m thinking of it, now that we took over the web request, I don’t even know how much more they’re gonna be using.
93 00:14:36.690 ⇒ 00:14:37.940 YvetteRuiz: For scheduling.
94 00:14:38.530 ⇒ 00:14:39.230 Amber Lin: Hmm.
95 00:14:40.500 ⇒ 00:14:42.800 Amber Lin: Yeah, I think we can look into that.
96 00:14:43.390 ⇒ 00:14:48.180 Amber Lin: Because they’re the folks who use this… like, they take off half
97 00:14:48.280 ⇒ 00:15:06.759 Amber Lin: of our usage, I would say, and I… I just really want to see if things has improved, because if there’s no benefit, they wouldn’t use Andy. So there has to be something. I think we can… I know there’s probably… you said there’s something transitioning in the team, so maybe you guys could start measuring the KPIs for that team?
98 00:15:07.450 ⇒ 00:15:15.820 YvetteRuiz: Yeah, I’m gonna have to follow up, because like I said, I mean, I think the reason that… I don’t think I know… the reason that they use Andy is specifically just for.
99 00:15:15.820 ⇒ 00:15:16.200 Amber Lin: beans.
100 00:15:16.200 ⇒ 00:15:31.480 YvetteRuiz: your zip code sheet, but we just recently went to a change to where all the web requests, that means our customers that go ask us for estimates on our website would normally go, those requests would go to them and they would schedule, but now they’re coming to my team now.
101 00:15:31.480 ⇒ 00:15:32.280 Amber Lin: Mmm.
102 00:15:32.280 ⇒ 00:15:38.349 YvetteRuiz: So I don’t even know if they’re gonna even be utilizing, Indy anymore, but I can… I can…
103 00:15:39.230 ⇒ 00:15:41.459 YvetteRuiz: I need to get more information on that end, Amber.
104 00:15:41.910 ⇒ 00:15:48.559 Amber Lin: Let us know, because if it’s transferred to your team, then your team will start to use the Andy for that feature.
105 00:15:49.230 ⇒ 00:15:49.940 Amber Lin: So…
106 00:15:49.940 ⇒ 00:15:50.670 YvetteRuiz: energy.
107 00:15:55.790 ⇒ 00:15:56.409 YvetteRuiz: Introduce yourself.
108 00:15:56.410 ⇒ 00:15:58.600 Uttam Kumaran: Yeah, I guess I…
109 00:15:58.740 ⇒ 00:16:17.270 Uttam Kumaran: Yeah, I guess one question I have, maybe, you know, I was just thinking about the transcript pieces, like, I don’t know, Janiece or Eva, as part of the training process, do you guys do, like, call reviews? And is there, like, a structured way you guys do that, or even if you can verbalize now, sort of, like.
110 00:16:17.350 ⇒ 00:16:27.790 Uttam Kumaran: what are the things that you’re reviewing in the call? I think that’s something that, you know, we could totally try to have, you know, augmented in some way. As we look through all the transcripts.
111 00:16:27.910 ⇒ 00:16:37.869 Uttam Kumaran: it would be great for every call to sort of have a little bit of a review. Just curious, like, how you guys do that today, like, what’s… what typically happens in that review process?
112 00:16:39.000 ⇒ 00:17:03.500 YvetteRuiz: Yeah, we have a QA pro… we have a QA process. We use a company named CallSource. Car Source monitors all our calls. Well, I didn’t say all our calls, a majority of the phone calls, not every single one of them. But they do, and we’ve created… we designed our own scorecard with what we want, you know what I mean? How the CSR should answer, the tran… you know, how they… how they handle that call flow. But we can share that with you.
113 00:17:03.500 ⇒ 00:17:07.159 YvetteRuiz: And they get reviewed. We have a dashboard for them, the calls are…
114 00:17:07.160 ⇒ 00:17:07.609 Uttam Kumaran: Great, okay.
115 00:17:07.619 ⇒ 00:17:10.339 YvetteRuiz: there that they’re monitored and all.
116 00:17:10.599 ⇒ 00:17:16.899 YvetteRuiz: that’s the thing, that’s the big thing, Udom, is, like, we’re currently using them, 8x8 sort of has,
117 00:17:16.900 ⇒ 00:17:17.460 Uttam Kumaran: Yes.
118 00:17:17.460 ⇒ 00:17:23.390 YvetteRuiz: grading system as well, and so I’m… we’re trying to… we’re right now in the middle of trying to figure out, okay.
119 00:17:24.210 ⇒ 00:17:34.380 YvetteRuiz: Does it make sense to be paying call source, or can 8x8 do it? Is there a better way that we can start managing and measuring those calls?
120 00:17:34.520 ⇒ 00:17:34.970 Amber Lin: Yeah.
121 00:17:34.970 ⇒ 00:17:35.520 Uttam Kumaran: Nope.
122 00:17:35.520 ⇒ 00:17:41.249 Amber Lin: Is that a big expense for you guys, to have them monitor the majority of those calls? You guys have a lot of calls.
123 00:17:42.390 ⇒ 00:18:04.159 YvetteRuiz: Yes, yes it is, but we had to go that direction, because for a company our size, I mean, you guys know how many phone calls, you already see the numbers that we go through. Before we went to call source, we weren’t even scratching the surface with listening to phone calls, you know what I mean? I mean, we were probably… because we were doing it in-house. We had one person listening to all these phone calls, and then to do the QA coachings.
124 00:18:04.160 ⇒ 00:18:14.480 YvetteRuiz: So we had to go to a company, because now we’re able to go in there and pick up trends, okay, where are the areas and stuff like that, but it is… it’s cost-effective, you know what I mean? But…
125 00:18:14.480 ⇒ 00:18:14.860 Uttam Kumaran: Yeah.
126 00:18:14.860 ⇒ 00:18:23.299 YvetteRuiz: So, Abyte has, again, some features in it, and now with AI, you know, with the whole transition with AI coming, I know that there’s.
127 00:18:23.300 ⇒ 00:18:32.619 Uttam Kumaran: Also, I wouldn’t be surprised if 8Byte has that offering, you know? So that’s something we can also talk with them. Yeah, maybe it’s the ability to consolidate, but I would also just be…
128 00:18:32.620 ⇒ 00:18:44.320 Uttam Kumaran: interested to see, like, if you guys like the scorecards that you’re seeing from there, or… because the thing with what’s going to happen with all these software tools, they’re gonna release something that goes to everybody, but you want to have an ABC-specific
129 00:18:44.320 ⇒ 00:18:59.919 Uttam Kumaran: like, scorecard, right? And so that’s the thing I’m curious, like, if it is effective, if there are limitations in, like, what the output is, because this, like, taking the transcript, running it through, like, an AI to get a little scorecard is very…
130 00:18:59.940 ⇒ 00:19:10.949 Uttam Kumaran: like, pretty basic thing for us to do. I don’t want to do it if it already exists somewhere, though. Like, if… because then you’re… now you have a third place to check, right? But if it… if there is a… if it does add a level up.
131 00:19:11.110 ⇒ 00:19:14.889 Uttam Kumaran: Or if it is more helpful in another way, then it’s worth considering.
132 00:19:15.420 ⇒ 00:19:26.350 YvetteRuiz: Absolutely, and so, yeah, so we worked with them because we wanted to design our own scorecard, so we did work with them to do that. The thing that we’re running into right now, Uten, because they did.
133 00:19:26.350 ⇒ 00:19:27.260 Uttam Kumaran: God.
134 00:19:27.260 ⇒ 00:19:36.440 YvetteRuiz: transition into AI, you know, listening to the phone calls, is soft skills are big for us, obviously, you know what I mean? We’re not, okay, check the box type of thing. We need to make sure that.
135 00:19:36.440 ⇒ 00:19:36.760 Uttam Kumaran: Yes.
136 00:19:36.760 ⇒ 00:19:43.289 YvetteRuiz: So, that is a big thing since they started using the AI that we were missing.
137 00:19:44.260 ⇒ 00:19:46.410 Uttam Kumaran: Okay, okay.
138 00:19:47.050 ⇒ 00:20:01.139 Uttam Kumaran: So yeah, maybe something we can consider, I think, once we look at the transcripts, and then see, like, we can put… I think we’re still working on getting the transcripts. We, like, there were some hiccups with the API. It’s also something I want to talk to the 8x8 team about.
139 00:20:01.140 ⇒ 00:20:08.620 Uttam Kumaran: But one of… a quick, like, test I want to do is just, like, try to see if we can produce an output, and yeah, maybe it is focused more on soft skills.
140 00:20:08.620 ⇒ 00:20:19.410 Uttam Kumaran: But more additionally, it also can be helpful for the trainers on, like, what to… what feedback to give, you know, things like that. So maybe something that I think we’ll look into.
141 00:20:19.410 ⇒ 00:20:32.749 YvetteRuiz: Yeah, no, definitely, that is huge. And if you want, I mean, we may be pressed for time today, I mean, you know, Janiece, you can share the call source dashboard with you and kind of give you an idea of what that all looks like.
142 00:20:32.750 ⇒ 00:20:42.569 Uttam Kumaran: Yeah, even just a screenshot, Janiece, or something, it’s just helpful. I kind of… I have a picture in my mind, but yeah, whatever you can share just gives us some context.
143 00:20:42.570 ⇒ 00:20:53.730 JanieceGarcia: Not a problem. I’ll do that. I’ll send you a couple screenshots of our card, and then I did send you a draft of what our QA scorecard is. I actually had it because I was working with a new hire today, so…
144 00:20:53.730 ⇒ 00:20:54.719 Uttam Kumaran: Oh, perfect, okay.
145 00:20:55.030 ⇒ 00:20:58.139 YvetteRuiz: And to your point, Udom, I mean, it does, it gives us, like.
146 00:20:58.140 ⇒ 00:20:58.600 Uttam Kumaran: Okay.
147 00:20:58.600 ⇒ 00:21:18.819 YvetteRuiz: what are the top missed items that the CSRs are missing, you know what I mean? What are they, what are they hitting, what are they missing, and stuff like that. And that’s all good information, but when you don’t have the soft skills in it, it’s just… that is like… I mean, that’s where your connections come with, right? So we know a lot of the times, our top ones are, oh, by the way, empathy.
148 00:21:18.820 ⇒ 00:21:21.839 YvetteRuiz: is only… you know what I mean? So, and…
149 00:21:21.840 ⇒ 00:21:22.360 Uttam Kumaran: Yeah.
150 00:21:22.360 ⇒ 00:21:28.839 YvetteRuiz: transition statement, I believe. So we always know what our top missed ones that we need to be focusing on with our CSRs.
151 00:21:29.170 ⇒ 00:21:29.900 Amber Lin: Huh.
152 00:21:30.640 ⇒ 00:21:31.760 Amber Lin: Sounds good.
153 00:21:31.890 ⇒ 00:21:35.469 Amber Lin: I’ll continue with this update.
154 00:21:35.770 ⇒ 00:21:50.409 Amber Lin: So, we’re at the start of December. I think we made good progress on mechanical. It’s fully rolled out. We made good progress on lawn and home improvement. Home improvement, we’re in initial testing, and lawn, we’re creating.
155 00:21:50.410 ⇒ 00:21:58.959 Amber Lin: We’re just adding that to Andy right now, we’re finishing up the last bits, and then the usage has improved.
156 00:21:59.200 ⇒ 00:22:00.230 Amber Lin: So…
157 00:22:00.690 ⇒ 00:22:13.730 Amber Lin: This week, our focus was, number one, the zip code database. So, Casey was able to add all the tables except for the inspector sheet, so that he’s working on that, and I think we’re…
158 00:22:13.940 ⇒ 00:22:28.350 Amber Lin: able to test it by end of week, and then I just said about the department updates, and lastly, on the CSR feedback, I think, Janiece and team has been really great. New ticketing system works well. We’ve been able to involve
159 00:22:28.460 ⇒ 00:22:34.769 Amber Lin: Tara and Brenda from Mechanical and Home Improvement, so to…
160 00:22:35.070 ⇒ 00:22:50.499 Amber Lin: help Janiece with her workload, and having the ticketing system means that we can talk about different tickets and assign them once it’s… oh, it’s in the central doc, but it’s not showing up, so it helps us,
161 00:22:51.020 ⇒ 00:22:53.620 Amber Lin: Triage responsibilities a lot better.
162 00:22:54.190 ⇒ 00:22:55.230 Amber Lin: So…
163 00:22:55.450 ⇒ 00:23:10.079 Amber Lin: Next week, our plan is to, one, work with the new mechanical and home improvement CSRs who has never used Andy, so that’s a working session, one to two, and also to start Lawn’s initial testing.
164 00:23:10.500 ⇒ 00:23:17.849 Amber Lin: And hopefully by next week, we can start testing the zip code database and have some initial insights from the transcripts.
165 00:23:18.880 ⇒ 00:23:32.310 Amber Lin: And this is just a quick view of the zip code database, and this is how we have it for the technicians. So each row will be a zip code, and then the person in that zip code.
166 00:23:33.930 ⇒ 00:23:42.080 Amber Lin: Before I end, I think I have a question. So, we were working on the lawn document.
167 00:23:42.090 ⇒ 00:23:54.530 Amber Lin: And they also have their own spreadsheet that’s sort of like an inspector sheet, sort of like a tech sheet, but just for lawn services, so lawn, tree, lawn mowing.
168 00:23:54.790 ⇒ 00:24:05.440 Amber Lin: Is this something that we keep separate, or is this something that we should work with them to add to our new zip code database? Because now Andy just has a lot of sources.
169 00:24:06.420 ⇒ 00:24:10.869 YvetteRuiz: I… my… the goal would be to have it in one… one location, you know?
170 00:24:10.870 ⇒ 00:24:11.530 Amber Lin: I mean, that…
171 00:24:11.530 ⇒ 00:24:21.070 YvetteRuiz: That’s the whole thing, is we knew that everybody had their own ways of doing it, but it would be good to combine that with what you guys are building right now.
172 00:24:21.070 ⇒ 00:24:35.000 Amber Lin: Okay, so next week, once Casey finishes the main setup, I’ll find a time with the lawn folks, and ask them how they work through this, and we’ll add that to our database.
173 00:24:35.580 ⇒ 00:24:37.259 YvetteRuiz: Awesome, love that.
174 00:24:37.990 ⇒ 00:24:38.650 Amber Lin: Yeah.
175 00:24:39.090 ⇒ 00:24:48.250 Amber Lin: That’s all. Let me note down my tasks. Can we find a time next week? I know you guys said UTAM to…
176 00:24:48.490 ⇒ 00:24:52.569 Amber Lin: To check UTAM’s availability next week, do you connect with 8x8?
177 00:24:53.900 ⇒ 00:24:55.700 Amber Lin: Trevor, do you want to be in that meeting?
178 00:24:56.950 ⇒ 00:25:02.450 YvetteRuiz: Is that whatsoever Did I want to what? I didn’t hear you, Amber, I’m.
179 00:25:02.450 ⇒ 00:25:09.140 Amber Lin: Did you want to be in the meeting with Utom and 8x8? I remember at the start of this call, you guys said you want to have a meeting.
180 00:25:09.140 ⇒ 00:25:18.129 YvetteRuiz: Yeah, I mean… I mean, I’m good. I just put it out there, like, if I… again, it’d be good just to talk, you know, be there to listen. Yeah. But, yeah.
181 00:25:18.130 ⇒ 00:25:33.279 Uttam Kumaran: We can coordinate the… for both of us, Sam and the 8-night person, and then worst case, Yvette, I’m happy to have the call if you’re busy. Yeah, I mean, afternoons next week are fine with me, so… as early as we can do them.
182 00:25:33.690 ⇒ 00:25:37.110 YvetteRuiz: Yeah, that’s exactly what I told him. I said, I don’t… I mean, as long as you guys connect…
183 00:25:37.110 ⇒ 00:25:37.670 Uttam Kumaran: tough.
184 00:25:37.800 ⇒ 00:25:40.560 Uttam Kumaran: But, like, Tuesdays onwards, I’m fine.
185 00:25:40.930 ⇒ 00:25:42.140 YvetteRuiz: juicy onwards. Okay.
186 00:25:42.140 ⇒ 00:25:42.850 Amber Lin: Okay.
187 00:25:43.360 ⇒ 00:25:44.900 Uttam Kumaran: Thank you.
188 00:25:45.230 ⇒ 00:25:55.420 YvetteRuiz: I’m gonna circle back with them, Utem, like I told them. I told them I was gonna meet with you guys today and just tell them, because that’s exactly what I told him. ASAP, even if I’m not there, I trust you guys to meet and then come back and just let me know what
189 00:25:56.410 ⇒ 00:26:00.820 YvetteRuiz: Whatever you guys found out, and what that all went, how that all went.
190 00:26:00.900 ⇒ 00:26:01.950 Uttam Kumaran: Cool.
191 00:26:01.950 ⇒ 00:26:02.270 Amber Lin: Okay.
192 00:26:03.020 ⇒ 00:26:04.150 Amber Lin: Sounds good.
193 00:26:07.350 ⇒ 00:26:32.120 YvetteRuiz: The only other… the other thing, I think I shared this with you, Utem, and I think I may have shared it with you, Amber. I went ahead and I just took all the data of all the questions that have been asked over the past month from the CSRs, and it was able to share a lot of good information, on there. You know, I mean, it looks like, I’m just reading it, you know, a lot of the heavy reliance, like, is going… is being used on the inspector sheets.
194 00:26:32.120 ⇒ 00:26:44.329 YvetteRuiz: the territories, that’s what a lot of the questions are coming through. Looks like that’s a big one right there. And then another one is just the clarifying the line of businesses, the specific routing and the availability… abilities.
195 00:26:44.430 ⇒ 00:26:47.940 YvetteRuiz: And then using Andy for a specific,
196 00:26:48.580 ⇒ 00:26:56.490 YvetteRuiz: Routing, qualifications, and then, there looks like there’s a lot of, like, little quick
197 00:26:56.490 ⇒ 00:27:02.170 YvetteRuiz: Like, words the way they’re using it, and sometimes it’s not recognizing what it’s asking.
198 00:27:02.170 ⇒ 00:27:22.390 YvetteRuiz: So, that’s one thing where I want to work with you, Amber, you guys, to see, okay, how can we… do we need to train them? It really gave us a lot of insight on what we need to work with our agents on, which is… was the goal, like, okay, what are… what are our agents asking, right? Like, what is it? So then that way we can go back and help if we need to, but it looks like…
199 00:27:22.390 ⇒ 00:27:29.760 YvetteRuiz: like, one example that it gave here, you know what I mean, was, like, a question of 3-story house, and it’s kind of like, okay, well, what does that mean?
200 00:27:29.910 ⇒ 00:27:37.659 YvetteRuiz: yeah, what are you asking, and stuff like that. So, I think that if we can maybe work on
201 00:27:38.210 ⇒ 00:27:51.960 YvetteRuiz: do you guys think, like, okay, do we need to train them better on how to ask better questions, or will these short keys work for them? I don’t know, because it looks like there’s a lot of stuff that it’s kind of not knowing to answer because of the way they’re asking the question.
202 00:27:51.960 ⇒ 00:28:00.870 Amber Lin: So, to answer on that, we have started a while ago to keep a abbreviations and alias list, so.
203 00:28:00.870 ⇒ 00:28:01.239 YvetteRuiz: Thank you.
204 00:28:01.240 ⇒ 00:28:25.419 Amber Lin: recently is someone asked, what is a estimator for this zip code? And Andy was so confused, because it knows inspector, but it doesn’t know estimator. But right now, after me and Janice met, we added an alias in the system of, okay, estimator, landscape designer, sales, estimate, inspector, all goes under inspector.
205 00:28:25.420 ⇒ 00:28:33.590 Amber Lin: So that’s some… that’s a list that we can keep, building, because everybody’s going to have different habits of saying things.
206 00:28:34.020 ⇒ 00:28:42.859 Amber Lin: So that’s something we can build on our end. I think in terms of Andy not knowing to answer, a lot of times it’s the structure of the questions.
207 00:28:43.360 ⇒ 00:29:02.490 Amber Lin: if it’s not a complete sentence, a lot of times Andy will get confused, and I don’t think there’s much we can change about it, it just… they don’t have time to type it out. But if it’s specific wording, spelling issues, that’s something we can fix with the IES and make sure Andy recognizes that this means this.
208 00:29:02.700 ⇒ 00:29:05.519 Amber Lin: So, I hope that answers your question.
209 00:29:05.760 ⇒ 00:29:16.439 YvetteRuiz: Yeah, no, no, no, it does, and you’re right, you know, the… some of the stuff, the way that they’re asking it, that’s, like, on us, like, that already gave us enough feedback to go back to make sure, like, hey, make sure when you’re
210 00:29:16.760 ⇒ 00:29:34.720 YvetteRuiz: say… ask the question, right? Like, click… but with the short, like, some of those short phrases or whatever, that’s another, you know, thing that I want to kind of just do a little bit more of a deep dive of specifically what are those things? You know, whether, like, you… the example that you gave, estimator, inspector.
211 00:29:35.190 ⇒ 00:29:39.390 YvetteRuiz: What other… what other, short phrases are they referring to?
212 00:29:39.390 ⇒ 00:29:56.239 Amber Lin: Yeah, totally. Let me just quickly share screen, we have a few minutes left. So this is the sheet that we built so far. I think we have more in the central doc, but for example, people will say services, or this, and that means service.
213 00:29:56.390 ⇒ 00:30:12.829 Amber Lin: So that’s a hiccup. So I think as feedback comes in, a lot of times, as Annie says, sorry, I don’t know, and then we look at the questions, like, oh, that’s what people are referring to, and then we update this sheet, and then people… and then we start to know, okay, what are…
214 00:30:12.930 ⇒ 00:30:19.690 Amber Lin: what are we actually referring to? So, let’s see… The N here, abbreviations.
215 00:30:21.030 ⇒ 00:30:24.620 Amber Lin: So we have… Bid, services…
216 00:30:24.620 ⇒ 00:30:32.560 YvetteRuiz: And it may be more on, now that we’re expanding to the other divisions, they have their little short keys, not just the pesto.
217 00:30:32.560 ⇒ 00:30:32.960 Amber Lin: I’m kidding.
218 00:30:32.960 ⇒ 00:30:39.699 YvetteRuiz: also be things that we… that’s why I want to go in there and deep dive, because I know some of them came up with, like, some pool stuff, some lawn stuff.
219 00:30:40.340 ⇒ 00:30:44.819 YvetteRuiz: some, you know, there’s other key steps, I think, that we just gotta keep on…
220 00:30:45.380 ⇒ 00:30:45.920 YvetteRuiz: that.
221 00:30:45.920 ⇒ 00:31:10.339 Amber Lin: Totally. And I think one last note on the different departments, we’ve seen recently feedback on, oh, who… which department covers this service? And now that we’re… I think we’re… lawn’s the last department we’re adding, to the customer service division, and after that, I do want to combine at least, okay, a master cover sheet of what goes to which department.
222 00:31:10.520 ⇒ 00:31:27.740 Amber Lin: combine the billing, combine the account management, and then we can work on the specific scheduling processes later, but once we comb… I think combining that, will fill the gaps in a lot of those departments, because LA only has so many documents compared to PEST.
223 00:31:28.120 ⇒ 00:31:31.989 YvetteRuiz: Yeah, yeah. Okay. Well, yeah, that would make total sense. Okay.
224 00:31:33.400 ⇒ 00:31:35.559 Amber Lin: Yep, that’s all on my end.
225 00:31:36.680 ⇒ 00:31:38.500 YvetteRuiz: Well, thank you for that.
226 00:31:38.700 ⇒ 00:31:41.909 YvetteRuiz: Thank you, I nude him.
227 00:31:41.910 ⇒ 00:31:43.639 Uttam Kumaran: Yeah, of course.
228 00:31:44.330 ⇒ 00:31:52.679 YvetteRuiz: Okay, well, you’re gonna get the pricing together for Matt. I’ll circle back with 8x8, just so we can get that meeting in the books for next week.
229 00:31:53.070 ⇒ 00:31:53.570 Uttam Kumaran: Bunk.
230 00:31:53.570 ⇒ 00:31:57.689 YvetteRuiz: And then, Janice, you already shared the QA stuff with, with, Udom, right?
231 00:31:57.700 ⇒ 00:32:04.160 JanieceGarcia: I sure did, I already shared it, and I already took screenshots while you guys were talking about the abbreviations and stuff, so…
232 00:32:04.160 ⇒ 00:32:06.930 Amber Lin: Yeah. Awesome.
233 00:32:07.250 ⇒ 00:32:07.909 JanieceGarcia: Thank you.
234 00:32:08.230 ⇒ 00:32:18.029 JanieceGarcia: And then the, I did want to ask a question, though, for the session for next week, we’re going to start with mechanical, or do you want us to mix?
235 00:32:18.630 ⇒ 00:32:21.960 JanieceGarcia: Between the two, home improvement and mechanical.
236 00:32:22.640 ⇒ 00:32:26.649 YvetteRuiz: I think mechanical, because they rolled them out completely. I don’t know if a home improvement.
237 00:32:26.650 ⇒ 00:32:27.250 JanieceGarcia: Home Improvement.
238 00:32:27.250 ⇒ 00:32:27.670 YvetteRuiz: It’s just…
239 00:32:27.670 ⇒ 00:32:28.430 JanieceGarcia: testing.
240 00:32:28.430 ⇒ 00:32:32.479 YvetteRuiz: Yeah, they’re just testing right now, they mechanicals, the people we want to stick with.
241 00:32:32.480 ⇒ 00:32:36.410 JanieceGarcia: Do you have certain ones? And I’ll go ahead and add them, too.
242 00:32:36.410 ⇒ 00:32:41.450 YvetteRuiz: I’ll let you… you put that together. I mean, that’s everybody in there. I did a…
243 00:32:41.900 ⇒ 00:33:01.210 YvetteRuiz: I did not add their overflow people, I just asked Tara right now, because, the mechanical overflow people, because Patricia was asking me, she says, hey, Jenny, because they’re in the queues, can we add them? So I’m going to go ahead and add them, so if you want to start, add them to the mix, too.
244 00:33:01.210 ⇒ 00:33:01.880 JanieceGarcia: Okay.
245 00:33:02.160 ⇒ 00:33:05.130 JanieceGarcia: Perfect. Alright, then I will do that.
246 00:33:05.740 ⇒ 00:33:07.350 JanieceGarcia: Perfect, perfect. Okay.
247 00:33:08.000 ⇒ 00:33:08.870 YvetteRuiz: Alrighty.
248 00:33:09.080 ⇒ 00:33:13.000 JanieceGarcia: Awesome. Well, I’ll get those invites sent out. I already have 3 people on mine, so…
249 00:33:13.760 ⇒ 00:33:14.490 YvetteRuiz: Okay, cool.
250 00:33:14.640 ⇒ 00:33:16.449 JanieceGarcia: Awful bean. Thank you.
251 00:33:16.450 ⇒ 00:33:17.080 Amber Lin: Thank you.
252 00:33:17.080 ⇒ 00:33:18.370 YvetteRuiz: Bye, bye!
253 00:33:18.670 ⇒ 00:33:19.489 Amber Lin: Thank you.
254 00:33:19.490 ⇒ 00:33:20.100 Samuel Roberts: Bye.