Meeting Title: ABC | Weekly KPI Review Date: 2026-03-16 Meeting participants: YvetteRuiz, JanieceGarcia, read.ai meeting notes, Yvette’s Notetaker (Otter.ai), Pranav, Amber Lin
WEBVTT
1 00:00:36.850 ⇒ 00:00:38.000 YvetteRuiz: Oh, me…
2 00:00:48.530 ⇒ 00:00:49.649 JanieceGarcia: Can you hear me, Yvette?
3 00:00:51.840 ⇒ 00:00:52.430 JanieceGarcia: Okay.
4 00:01:00.390 ⇒ 00:01:04.209 JanieceGarcia: Why my real password is all of a sudden not working.
5 00:01:05.519 ⇒ 00:01:06.779 YvetteRuiz: It’s not working.
6 00:01:06.920 ⇒ 00:01:07.690 JanieceGarcia: -
7 00:01:09.990 ⇒ 00:01:17.569 JanieceGarcia: I’m gonna try it again. I was like, maybe I’m typing something wrong, I don’t… Never changed that password?
8 00:01:18.860 ⇒ 00:01:19.550 JanieceGarcia: Oh, man.
9 00:01:19.550 ⇒ 00:01:26.180 YvetteRuiz: I felt dumb the other day when I was saying that I couldn’t get into Dream. I forgot that I had already logged in and changed my password.
10 00:01:26.180 ⇒ 00:01:32.060 JanieceGarcia: Oh, that reminds me. So, at least I won’t… hopefully I won’t forget.
11 00:01:33.410 ⇒ 00:01:41.340 YvetteRuiz: Yeah, I know, Adita jumped in, and she was all like, no, it’s… I mean, it looks… seems to be okay, and
12 00:01:41.620 ⇒ 00:01:48.369 YvetteRuiz: She was like, have you changed your password? And I was just like, shit, I did, I totally forgot about that.
13 00:01:54.970 ⇒ 00:01:55.799 Pranav: Good mornin’!
14 00:01:56.040 ⇒ 00:01:57.449 YvetteRuiz: Good morning, how are you?
15 00:01:57.450 ⇒ 00:01:58.310 JanieceGarcia: Warning!
16 00:01:58.460 ⇒ 00:02:00.420 Pranav: I’m good, I’m good. How was the weekend?
17 00:02:01.930 ⇒ 00:02:05.659 YvetteRuiz: It was good, it was good. How about you?
18 00:02:06.320 ⇒ 00:02:11.060 Pranav: Pretty good, pretty good. I’m actually, planning a move to Austin later this summer.
19 00:02:11.690 ⇒ 00:02:16.359 YvetteRuiz: Oh, how exciting is it? Alright, so we get to meet you in person!
20 00:02:16.360 ⇒ 00:02:18.720 Pranav: Exactly, we’ll definitely plan that.
21 00:02:19.150 ⇒ 00:02:22.330 Pranav: Hopefully in June, maybe end of June.
22 00:02:23.050 ⇒ 00:02:32.980 YvetteRuiz: Oh, okay, cool! That’s gonna be exciting, yeah. And then you can, when you move down there, you can come up to our office, too, in San Antonio. I mean, come down to our office in San Antonio.
23 00:02:32.980 ⇒ 00:02:33.770 Pranav: God!
24 00:02:33.770 ⇒ 00:02:36.169 YvetteRuiz: Hi, Amber.
25 00:02:37.610 ⇒ 00:02:39.550 JanieceGarcia: That’s awesome, Pranav.
26 00:02:39.550 ⇒ 00:02:48.040 Pranav: Yeah, yeah, I love Austin. I used to live there, actually. And so, yeah, Amber, I was just telling them how I’m moving to Austin this summer.
27 00:02:48.290 ⇒ 00:02:51.839 Amber Lin: Wow. Wait, permanently, or just for the summer?
28 00:02:52.020 ⇒ 00:02:53.060 Pranav: Permanently.
29 00:02:53.060 ⇒ 00:02:54.359 Amber Lin: Oh, that’s so exciting!
30 00:02:54.800 ⇒ 00:03:07.340 Amber Lin: And then we’ll have… we’ll have an Austin office, because for… for me, I’m in LA, and we… I have about 4 people around me that’s in LA, so if we get an Austin office, that’ll be cool, too.
31 00:03:07.340 ⇒ 00:03:09.519 Pranav: Yeah, there’s some hubs forming, for sure.
32 00:03:09.960 ⇒ 00:03:12.610 YvetteRuiz: Exciting.
33 00:03:12.610 ⇒ 00:03:13.859 JanieceGarcia: That is exciting.
34 00:03:14.300 ⇒ 00:03:15.010 YvetteRuiz: Okay.
35 00:03:15.900 ⇒ 00:03:32.879 Pranav: Yeah, there’s a couple things that I wanted to talk through, and then, you know, if you guys have anything top of mind, we can go through those as well. Three things is, I kind of just want to give you guys a little bit more, just, like, insight to what we’re working on week to week. And so, I’m just gonna share our,
36 00:03:33.400 ⇒ 00:03:36.059 Pranav: My screen real quick, just to show you guys.
37 00:03:36.790 ⇒ 00:03:42.800 Pranav: are linear, just so you can see, like, some of the dev work we’re doing. I’ll explain everything, too.
38 00:03:43.110 ⇒ 00:03:47.250 Pranav: Right here.
39 00:03:49.010 ⇒ 00:03:55.580 Pranav: Yeah, so right here, we have a few things in progress, you’ll notice with just, like…
40 00:03:56.320 ⇒ 00:04:11.519 Pranav: these, like, upper branders, like, the master migration is the biggest thing that we’re working on right now, and we’re gonna wrap up by end of next week. End of this week, though, is where I feel really confident about just, like.
41 00:04:11.670 ⇒ 00:04:16.770 Pranav: actually shipping all the development stuff that we need to get done. And then next week, I think.
42 00:04:16.940 ⇒ 00:04:21.489 Pranav: If all goes well, we could probably even get the…
43 00:04:21.630 ⇒ 00:04:30.609 Pranav: we can probably have the CSRs using the newly migrated AND as early as, like, Tuesday or Wednesday.
44 00:04:31.300 ⇒ 00:04:39.760 Pranav: our plan is, is that we’ll have all the code shipped by Friday this week, so that on Monday, you guys can do, like, a final QA,
45 00:04:39.790 ⇒ 00:04:57.619 Pranav: pass, you know, just ask a few questions, maybe certain edge cases, that come to mind, and then right after that, we’ll just ask for your guys’, like, thumbs up, and then we’ll just, fully ship this into the production environment of where CSRs are using Andy.
46 00:04:57.620 ⇒ 00:04:58.220 YvetteRuiz: Perfect.
47 00:04:58.800 ⇒ 00:05:03.799 Pranav: So, yeah, that’s just quick. Let me stop sharing my screen.
48 00:05:04.670 ⇒ 00:05:09.110 Pranav: But… Yeah, so that was one thing. Another thing is,
49 00:05:09.220 ⇒ 00:05:19.590 Pranav: Janice, we were talking about with, like, the central docs, like, the restructuring, just getting comments on that. Yes. How are things looking, like, for that? Are we still, like, good to go for tomorrow to have that discussion?
50 00:05:19.590 ⇒ 00:05:20.300 JanieceGarcia: Tomorrow.
51 00:05:20.850 ⇒ 00:05:21.810 JanieceGarcia: Yes. Okay.
52 00:05:22.990 ⇒ 00:05:29.209 Pranav: Perfect, perfect. And then… yeah, so…
53 00:05:29.820 ⇒ 00:05:44.760 Pranav: I kind of covered, like, my third thing, which was just, like, the migration status, and so… yeah, we’re gonna do our internal QA this week, while also just shipping the code. Next week, we’ll get your guys’ final sign-off on that, and then…
54 00:05:45.200 ⇒ 00:06:00.309 Pranav: what we’ll… also, on Thursday this week, I’ll talk about a bunch of the different projects that we scoped out going forward to further increase accuracy, help with, like, this triage system, which has been a little bit cumbersome.
55 00:06:00.600 ⇒ 00:06:12.929 Pranav: And then, also, just with, like, better reporting. So, I want you guys to, like, have, like, the best dashboards for every single thing. We have a few ideas there,
56 00:06:13.050 ⇒ 00:06:20.809 Pranav: One of them being those, like, the weekly recap. What are the categories we’re seeing? We’re gonna create that dashboard for you guys.
57 00:06:21.210 ⇒ 00:06:35.829 Pranav: I’ll have a lot more information on that on Thursday, just refining a few different things, and then with that, we’ll talk about, like, the timelines for that. We’ve talked about, like, with this migration that we’ve built, we can move a lot faster on a lot of these things, so, like…
58 00:06:35.830 ⇒ 00:06:44.490 Pranav: Instead of thinking about months, we can think about weeks. And so, yeah, pretty exciting stuff. So, we’ll, we’ll talk about that on Thursday.
59 00:06:45.210 ⇒ 00:06:52.429 YvetteRuiz: Perfect. That kind of aligns with what Janiece and I were talking about this morning, you know, because as you know.
60 00:06:52.780 ⇒ 00:07:15.599 YvetteRuiz: she is now having one-on-ones with the trainers and the support managers, and part of that was, because after this meeting, Pranad, just so you know, we’re going to pause on meeting with the group, because Janiece is meeting with them one-on-one now, and part of that is going through the central docs and making sure that everything is right, what are we seeing, and then doing live testing at that time.
61 00:07:15.600 ⇒ 00:07:27.640 YvetteRuiz: But then also, is running those reports, the dashboards, I need her to get really familiar with that and say, okay, here’s your last week usage, here’s everybody who’s using it, here’s everybody who’s not.
62 00:07:27.670 ⇒ 00:07:32.839 YvetteRuiz: Why? You know what I mean? And really start drilling down to, okay.
63 00:07:33.200 ⇒ 00:07:50.119 YvetteRuiz: what is it? Because we’re going to hear things like, they don’t trust it, they’re still going to their docs, all those type of things, in which the goal is to trust in Andy, to make sure that Andy’s doing it. If it’s not, and if they’re not, why aren’t they, right? And if it’s something that’s not working, then we need to know right away so we can do it.
64 00:07:50.120 ⇒ 00:08:07.630 YvetteRuiz: But like I told Janice earlier, we need to think, again, with the end in mind, right? What’s our end goal, right? Our end goal is, when we hire new hires, we need to ramp them up really, really quick, so we need to make sure that the starting base is right, right? Like, the accuracy, the time, the response time and everything. And then, of course.
65 00:08:07.630 ⇒ 00:08:30.860 YvetteRuiz: Average handle time, is that coming down? But that… those are… those are, like, what needs to start happening, but right now, the build is, and this is what she’s… the key things that she’s doing on her one-on-ones right now. So, the dashboard is going to be one thing, so thank you for sharing that, because, you know, knowing the reasons, what are they… what are they asking, right, is really going to give us some good insight, and then also the usage, and then other things that we can start utilizing that dashboard for.
66 00:08:33.039 ⇒ 00:08:43.709 Pranav: So with those dashboards, too, I think, Janice, this is… this is actually great, because, we can talk about exactly which ones you want to prioritize. I think…
67 00:08:43.709 ⇒ 00:08:56.709 Pranav: I came up with, like, 6 or 7 dashboards that I think could be useful, but probably for something like onboarding, for something like usage specifically, those are maybe things we want to prioritize, so… Yes.
68 00:08:56.929 ⇒ 00:09:03.789 Pranav: Let me actually maybe… if, there’s no other topics, I can also go into, like.
69 00:09:04.419 ⇒ 00:09:05.669 Pranav: Sorry, did I just interrupt?
70 00:09:05.670 ⇒ 00:09:14.000 YvetteRuiz: No, I was just gonna tell you, what we had listed here was on… what I had listed here for hers, one of them is, like, the onboarding piece of it, the new hire piece.
71 00:09:14.060 ⇒ 00:09:29.029 YvetteRuiz: The average handle time, and then the comparison, like, with Andy, you know what I mean? Because that’s what we talked about once by, are they utilizing Andy to get their answers? And then the hold count, right? Because I was looking at last month’s KPIs.
72 00:09:29.030 ⇒ 00:09:37.789 YvetteRuiz: And, you know, I… and I’m just specifically, because these are top of mind right now, 2 and Pest are big drivers of that. I mean, we had some that were, like, almost at
73 00:09:37.790 ⇒ 00:09:39.020 YvetteRuiz: Triple digits.
74 00:09:39.020 ⇒ 00:09:53.520 YvetteRuiz: It’s like, why? You know what I mean? And some of them are new hires, some of them are not. It’s like, we’ve got to get to the level to where we’re drilling in there and seeing, okay, what is driving that? So those are just kind of some of the, the KPIs that I really want to start,
75 00:09:53.560 ⇒ 00:09:55.020 YvetteRuiz: diving into.
76 00:09:55.240 ⇒ 00:10:04.300 Pranav: Cool. Yeah, so that’s actually super useful, and it kind of aligns with one of the projects that we’re… that we’re… that I’m scoping out, which is…
77 00:10:04.660 ⇒ 00:10:14.369 Pranav: how can we use transcripts to assess where maybe CSRs should have used Andy? Like, where is, like, you know, that gap right now? Because I’m… my…
78 00:10:14.610 ⇒ 00:10:29.790 Pranav: easy wins right now is to figure out where are people using, or not using Andy, but they’re asking the exact questions that Andy could give the exact right answer for. Yep. And so that brings in the transcripts, right? Like, so we pull in all these transcripts from the different CSRs,
79 00:10:29.790 ⇒ 00:10:44.340 Pranav: we can do a bunch of different sorting there to give you guys, like, actionable, like, insights about, like, okay, which department, which even, like, maybe trainer are they under, to, like, talk about, like, hey, you can give this, Janiece, you can give this specific feedback to this trainer.
80 00:10:44.340 ⇒ 00:10:51.300 Pranav: That would be super, I think, helpful to kind of just, like, drive usage. But then on top of that, it’s…
81 00:10:51.670 ⇒ 00:10:54.170 Pranav: We’re gonna…
82 00:10:54.370 ⇒ 00:11:11.289 Pranav: we’re gonna categorize the questions that are being asked by the CSRs into 3 different buckets. One thing is gonna be, like, you could have asked Andy this right now, and it would have given you the right answer. One other thing is, oh, this is probably, like, an edge case where, you know, we don’t ever see Andy
83 00:11:11.410 ⇒ 00:11:26.119 Pranav: wanting to have this go… or maybe not ever is the right answer, but, like, it’s okay that Andy’s not answering these type of questions right now. There’s certain, maybe, questions that we can talk about that maybe we don’t want Andy answering, because it’s going to be a huge lift to get that into the central dock.
84 00:11:26.120 ⇒ 00:11:34.859 Pranav: Or maybe it’s not really applicable to be in the Central God. And then there’s gonna be something that’s gonna be useful a lot for us, is about where is that knowledge gap of, like.
85 00:11:34.860 ⇒ 00:11:44.459 Pranav: yeah, CSRs can’t get this information reliably from the central doc right now. And so, which each of those three buckets, I think, is gonna be, like, a lot of useful stuff.
86 00:11:44.550 ⇒ 00:11:46.599 Pranav: With that first bucket of…
87 00:11:46.940 ⇒ 00:12:00.160 Pranav: Andy has this information right now, Janice, you can then take that information and be like, hey, trainers in mechanical, hey, trainers in pests. These are the things that I’m seeing across of all our conversations.
88 00:12:00.240 ⇒ 00:12:12.620 Pranav: and 50%, 40%, whatever the percentage is, are questions that could have been asked to Andy. And then we’ll also give top 10 categories about, like, okay, these are the 10 categories of, like.
89 00:12:12.920 ⇒ 00:12:25.250 Pranav: maybe right now, only 10% of you guys are asking Andy the questions within this category, but all of these questions here could have been asked to Andy, and you would have got the right answer. I think that’s easier to be like.
90 00:12:25.280 ⇒ 00:12:38.399 Pranav: you know, you guys aren’t using Andy, why, like, start using it? We can start giving them… we can start giving them actionable direction about, like, hey, for these type of comments, always ask Andy, because it’s always going to give you the right answer.
91 00:12:38.600 ⇒ 00:12:39.520 JanieceGarcia: Yep. Yep.
92 00:12:40.350 ⇒ 00:12:41.690 Pranav: Cool.
93 00:12:41.690 ⇒ 00:12:42.480 JanieceGarcia: That’s awesome.
94 00:12:42.700 ⇒ 00:12:47.739 Pranav: Yeah, Yvette, Janice, we’ll talk a little bit about just, like, how it looks in terms of
95 00:12:48.150 ⇒ 00:13:05.600 Pranav: building some type of pipeline on y’all’s end for pulling in the transcripts into a place where we can then process them. Because this will be great for… to do, like, a historical, analysis of how the transcripts have gone for the past 3 months, 4 months, whatever.
96 00:13:05.600 ⇒ 00:13:08.570 Pranav: But then, going forward, we’d want to get, like.
97 00:13:08.900 ⇒ 00:13:20.549 Pranav: weekly insights on this. So this would then turn into, like, a dashboard of, like, hey, this was last week’s conversations, what percent were still, like, gaps in terms of CSRs not using ANDI when they could have? Yeah.
98 00:13:20.550 ⇒ 00:13:21.080 JanieceGarcia: Thanks.
99 00:13:21.790 ⇒ 00:13:42.559 YvetteRuiz: Yep, no, that’s everything that… that’s very cool, and being able to tie that information is key, because I know that early on we talked about it being able to provide us that type of information where it goes to. Is this an over… because I think even big picture, it’s going to say, okay, is this overall? Like, I mean, are all our CSRs asking that same question, or is it specific, or is it a specific.
100 00:13:42.560 ⇒ 00:13:42.890 JanieceGarcia: window.
101 00:13:42.890 ⇒ 00:13:49.470 YvetteRuiz: apartment type of thing. And of course, the other, the other piece, like I told Janice, again, thinking with the end in mind is.
102 00:13:49.520 ⇒ 00:14:06.410 YvetteRuiz: you know, Bobby’s big vision is our agents being expert at all our lines of business, and how are we able to be able to… to get them those answers quickly, right? To be able to have cross-trained agents, to be able to answer questions like that. I mean, that is like a diamond right there.
103 00:14:06.780 ⇒ 00:14:22.910 Pranav: Yeah, yeah. And Andy, currently, right now, is, you know, it’s giving information across all these departments, so yeah, now giving… finding these gaps for why people aren’t using it for certain things, I think that’s gonna be a huge key for just, like, increasing usage.
104 00:14:22.960 ⇒ 00:14:29.809 Pranav: Yeah. Because I’m just thinking if, like, if I’m in a meeting with, like, a bunch of people, and we’re getting just, like, broad, just, you know, hey.
105 00:14:29.810 ⇒ 00:14:44.129 Pranav: use Andy, it’s a lot harder to even convince me to, like, use it, unless, like, someone maybe even calls me out, or calls a group of people, a small group of people, and they’re like, hey, why weren’t you guys using Andy for X, Y, and Z?
106 00:14:44.130 ⇒ 00:14:49.889 Pranav: then it’s like, that’s gonna be in your brain. Next time you are in a call, you’re gonna use Andy for that.
107 00:14:50.110 ⇒ 00:14:51.670 YvetteRuiz: Yeah, for sure.
108 00:14:51.670 ⇒ 00:14:52.149 JanieceGarcia: We have back…
109 00:14:52.150 ⇒ 00:15:06.509 YvetteRuiz: You know, we don’t know why they’re not using it. I mean, there’s various reasons. That’s kind of why I put that in the usage piece of it, to start asking questions, right? And of course, with the data that we’re able to pull out of it, now we can even get more granular, but it’s always good to know.
110 00:15:06.870 ⇒ 00:15:10.000 YvetteRuiz: Why aren’t they… Why aren’t they?
111 00:15:10.300 ⇒ 00:15:10.730 Pranav: Yeah.
112 00:15:11.180 ⇒ 00:15:11.780 Pranav: Definitely.
113 00:15:12.900 ⇒ 00:15:22.850 JanieceGarcia: Awesome. So, can I ask, okay, we had the, the report is sent, right? So we do get that,
114 00:15:23.350 ⇒ 00:15:29.570 JanieceGarcia: But we had one of the trainers come through and say that she’s not able to see a specific person.
115 00:15:29.710 ⇒ 00:15:34.299 JanieceGarcia: I did go in there as well, and I can’t see him.
116 00:15:34.520 ⇒ 00:15:37.140 JanieceGarcia: What am I doing wrong?
117 00:15:37.640 ⇒ 00:15:38.899 JanieceGarcia: on our report.
118 00:15:40.100 ⇒ 00:15:41.919 Pranav: Are you referring.
119 00:15:41.920 ⇒ 00:15:47.760 Amber Lin: to the report in, in Vril, or the one that I signed up for Monday?
120 00:15:48.030 ⇒ 00:15:48.560 JanieceGarcia: In real.
121 00:15:49.650 ⇒ 00:15:56.139 Amber Lin: I see. Can you pull up the view that you’re looking, and then we can help point you to…
122 00:15:56.410 ⇒ 00:15:58.440 Amber Lin: Where the individual person is.
123 00:16:10.750 ⇒ 00:16:11.909 JanieceGarcia: Can y’all see that?
124 00:16:13.960 ⇒ 00:16:14.570 YvetteRuiz: Yep.
125 00:16:25.180 ⇒ 00:16:26.440 JanieceGarcia: Like, if we’re seeing.
126 00:16:26.440 ⇒ 00:16:26.890 Amber Lin: Bookies.
127 00:16:26.890 ⇒ 00:16:30.940 JanieceGarcia: people, are these literally the only ones that have used Andy?
128 00:16:32.670 ⇒ 00:16:35.170 Amber Lin: On… for that week.
129 00:16:35.920 ⇒ 00:16:36.650 Amber Lin: Yes.
130 00:16:36.650 ⇒ 00:16:39.109 YvetteRuiz: The date range, so the 10th through the 16th?
131 00:16:39.110 ⇒ 00:16:39.950 Pranav: Yeah.
132 00:16:41.780 ⇒ 00:16:47.379 Pranav: So this might be able to switch to, like, all time, if you wanted to see everybody that’s ever used Andy.
133 00:16:48.130 ⇒ 00:16:52.789 YvetteRuiz: Where can… is there in here, Pranelle, a way we can do, like, week-to-week comparison?
134 00:16:53.610 ⇒ 00:16:54.420 JanieceGarcia: Yeah.
135 00:16:54.420 ⇒ 00:16:54.800 Pranav: Yeah.
136 00:16:54.800 ⇒ 00:16:57.540 YvetteRuiz: Is it… can we… I just… I want to be able to.
137 00:16:57.540 ⇒ 00:17:00.269 Amber Lin: Might need to log in, cause that…
138 00:17:00.410 ⇒ 00:17:09.440 Amber Lin: That icon right here, that’s how you can do the… Week-to-week comparison, yeah.
139 00:17:10.270 ⇒ 00:17:17.970 Amber Lin: Oh, maybe select 7 days, because we can’t really do old-time comparisons. Maybe that, and then we can compare?
140 00:17:20.450 ⇒ 00:17:23.509 Amber Lin: If you select the last 14 days.
141 00:17:24.300 ⇒ 00:17:25.450 Amber Lin: Down there.
142 00:17:25.819 ⇒ 00:17:34.479 Amber Lin: Yeah, and then you can click on the compare, and you can select what you want to compare with, and that will give you, okay, so what was it like?
143 00:17:35.780 ⇒ 00:17:38.059 YvetteRuiz: Previous period to this period?
144 00:17:38.340 ⇒ 00:17:38.900 Pranav: Yes.
145 00:17:39.450 ⇒ 00:17:41.039 Pranav: You can see, like, that delta field.
146 00:17:41.180 ⇒ 00:17:45.460 Pranav: Which shows… The actual number and the percentage.
147 00:17:46.000 ⇒ 00:17:51.990 Amber Lin: Yeah. Is what you want to see, so different weeks of usage? Do you want it on a column?
148 00:17:53.960 ⇒ 00:18:17.240 YvetteRuiz: just something easy to read to be able to compare, so when she goes into this meeting, she’s able to go in there and say, okay… because I think that’s a great way to measure, you know what I mean? Like, okay, your team, you know, here’s what the usage was last week, this is what was the previous week, right? And then you go even more granular to go in there and see, okay, here’s your team, and how many they’ve, you know, how much, active… I mean, how much they’ve used it.
149 00:18:17.250 ⇒ 00:18:21.559 YvetteRuiz: That’s kind of what we want to be able to see, and then really start drilling down to.
150 00:18:21.920 ⇒ 00:18:29.619 YvetteRuiz: what’s going on? And then, of course, once we have the even granular data showing, you know, hey, these are all the questions that, you know what I mean.
151 00:18:29.810 ⇒ 00:18:30.170 JanieceGarcia: What was that?
152 00:18:30.170 ⇒ 00:18:31.449 YvetteRuiz: Asked or weren’t asked.
153 00:18:31.640 ⇒ 00:18:48.619 Amber Lin: Gotcha, okay. I think I can… let me see if I can pull up a view real quick. That’s, I think, what you want to see. So… if I can share screen, I can show you what it will look like.
154 00:18:55.790 ⇒ 00:19:06.300 Amber Lin: So… Right here. So… So, right here, I…
155 00:19:07.020 ⇒ 00:19:16.289 Amber Lin: I think, Janiece, you can also see this little time icon right here. I first clicked on… you were in this view, I clicked on this icon.
156 00:19:16.420 ⇒ 00:19:31.819 Amber Lin: To make it by department. And then I pulled in this little time icon right here. I can make this a view and share this with you, but then you can… you can see, okay, what was it like for the last months?
157 00:19:32.030 ⇒ 00:19:42.450 Amber Lin: So, let’s say for this person, what was the usage like for the different weeks? So, we can do past month.
158 00:19:43.440 ⇒ 00:19:47.420 Amber Lin: And then we’ll be able to see, this is the most recent week.
159 00:19:47.820 ⇒ 00:19:51.429 Amber Lin: This is… for this person.
160 00:19:51.550 ⇒ 00:19:53.270 Amber Lin: What was it like?
161 00:19:53.590 ⇒ 00:19:55.980 Amber Lin: In the last weeks.
162 00:19:56.340 ⇒ 00:19:59.469 Amber Lin: Did they use it, and what was it, like.
163 00:20:01.390 ⇒ 00:20:07.089 Amber Lin: So, would this view be helpful? If so, I can definitely share this with you.
164 00:20:07.960 ⇒ 00:20:11.639 JanieceGarcia: That would, I mean, that does definitely give the week-over-week.
165 00:20:11.640 ⇒ 00:20:12.930 YvetteRuiz: And the agent.
166 00:20:12.930 ⇒ 00:20:16.180 JanieceGarcia: comparison, and the agent, and the department they’re in.
167 00:20:16.180 ⇒ 00:20:20.030 Amber Lin: Yeah, if you want to see, like, the percentage, we can do that as well.
168 00:20:20.560 ⇒ 00:20:21.100 JanieceGarcia: Okay.
169 00:20:21.230 ⇒ 00:20:22.080 JanieceGarcia: Yes.
170 00:20:24.600 ⇒ 00:20:25.310 Amber Lin: Cool.
171 00:20:26.000 ⇒ 00:20:34.570 JanieceGarcia: And with that, also noticing that there’s still a lot of… unknowns?
172 00:20:35.250 ⇒ 00:20:43.130 JanieceGarcia: But we did go in, and we updated their email address, we updated all of that. Yvette and I went through that entire sheet.
173 00:20:43.940 ⇒ 00:20:47.199 JanieceGarcia: an updated… But they’re still on there.
174 00:20:48.470 ⇒ 00:20:49.660 JanieceGarcia: I was unknown.
175 00:20:50.140 ⇒ 00:20:56.109 Amber Lin: Yeah, let me… let us check with Casey and the team to see if we can get that fixed.
176 00:21:04.870 ⇒ 00:21:07.900 JanieceGarcia: So, and I, I do, I want to make sure that we’re…
177 00:21:08.600 ⇒ 00:21:14.519 JanieceGarcia: They’re in the right groups and where they need to be, so it’s being counted correctly.
178 00:21:14.760 ⇒ 00:21:15.350 Pranav: Yup.
179 00:21:17.160 ⇒ 00:21:17.710 JanieceGarcia: Okay.
180 00:21:18.760 ⇒ 00:21:30.300 JanieceGarcia: And I was gonna ask, I feel crazy, it was definitely user error. I was struggling with logging in, I didn’t know what I was doing wrong, but I just realized it. I just needed y’all right there to watch.
181 00:21:33.200 ⇒ 00:21:34.999 Pranav: Login for… real?
182 00:21:35.000 ⇒ 00:21:36.640 JanieceGarcia: For real.
183 00:21:36.640 ⇒ 00:21:37.340 Pranav: Yeah, yeah.
184 00:21:39.820 ⇒ 00:21:40.450 JanieceGarcia: All good.
185 00:21:41.750 ⇒ 00:21:44.510 Pranav: Yeah, I think Rill is gonna be super…
186 00:21:44.640 ⇒ 00:21:51.960 Pranav: super beneficial for you and I to talk about, Janiece, just because, like, we have all these, like, additional dashboards that we want to build, so… yeah.
187 00:21:52.390 ⇒ 00:22:00.690 Pranav: Honestly, me too, I need to just, like, make sure I understand, like, the ins and outs of real, and so I’ll do that, and then we can… we can talk about…
188 00:22:01.080 ⇒ 00:22:12.409 Pranav: how… because even what Amber’s just showing right now, like, I feel like she has a really good understanding of, like, how real works, and just, like, building, you know, certain dashboards, certain filters on the fly, and so…
189 00:22:12.410 ⇒ 00:22:12.930 JanieceGarcia: Great.
190 00:22:13.220 ⇒ 00:22:16.699 Pranav: We’ll make sure that we’re all at that… at that point soon.
191 00:22:17.550 ⇒ 00:22:18.140 JanieceGarcia: Okay.
192 00:22:18.250 ⇒ 00:22:19.120 JanieceGarcia: Perfect.
193 00:22:20.260 ⇒ 00:22:32.659 Amber Lin: Awesome. Janice, I just shared the link with you. Let me know if that works, and we can… I can also make that into what we send out weekly, so let me know how it looks on your end.
194 00:22:35.670 ⇒ 00:22:39.580 JanieceGarcia: And then you just do the drop-downs to actually find the people. Yep.
195 00:22:40.840 ⇒ 00:22:41.490 Amber Lin: Awesome.
196 00:22:41.490 ⇒ 00:22:49.039 JanieceGarcia: So it gives us the total exchanges, and then, in… in all, but then you have it broken down for the weeks. Yep.
197 00:22:49.340 ⇒ 00:22:49.900 Amber Lin: Yeah.
198 00:22:51.390 ⇒ 00:22:52.220 Amber Lin: Cool.
199 00:22:56.430 ⇒ 00:22:58.429 JanieceGarcia: And wow, it already shows that.
200 00:22:59.420 ⇒ 00:23:02.030 JanieceGarcia: Even what’s been used today, as well.
201 00:23:03.820 ⇒ 00:23:05.550 Amber Lin: Yeah, we sync it pretty…
202 00:23:05.550 ⇒ 00:23:05.870 YvetteRuiz: Thank you.
203 00:23:07.390 ⇒ 00:23:07.980 Amber Lin: Yeah.
204 00:23:10.880 ⇒ 00:23:13.230 JanieceGarcia: So, yeah, I… I like that.
205 00:23:13.600 ⇒ 00:23:14.360 YvetteRuiz: Awesome.
206 00:23:14.360 ⇒ 00:23:14.910 JanieceGarcia: Ben.
207 00:23:20.570 ⇒ 00:23:27.140 JanieceGarcia: Yes, it will just be really good to have the ones, because like I said, there’s still quite a bit that’s under
208 00:23:27.330 ⇒ 00:23:29.699 JanieceGarcia: The unknowns, and they’re not…
209 00:23:30.410 ⇒ 00:23:31.410 JanieceGarcia: unknowns.
210 00:23:31.610 ⇒ 00:23:32.210 Pranav: Yep.
211 00:23:33.040 ⇒ 00:23:33.680 JanieceGarcia: So…
212 00:23:38.320 ⇒ 00:23:39.370 YvetteRuiz: Yep.
213 00:23:40.440 ⇒ 00:23:41.210 JanieceGarcia: Perfect.
214 00:23:42.990 ⇒ 00:23:50.220 Pranav: Cool. And Janice, I’ll, that should be a pretty quick fix, so I’ll just message, in that, like, Google chat.
215 00:23:50.370 ⇒ 00:23:53.000 Pranav: Group check. Okay. Yeah, when that’s fixed.
216 00:23:53.400 ⇒ 00:23:55.480 JanieceGarcia: Okay, perfect. Thank you.
217 00:23:55.680 ⇒ 00:23:56.220 Pranav: Yeah.
218 00:23:57.000 ⇒ 00:24:00.100 YvetteRuiz: And then my last question was on the speed.
219 00:24:00.340 ⇒ 00:24:10.809 YvetteRuiz: Pranav. So we’ll start, kind of, getting that data as well, with the improvements of the speed, the response time.
220 00:24:11.160 ⇒ 00:24:27.900 Pranav: Yeah, so I showed a little bit of just, like, preliminary, results with Jace last week, and so we were seeing, like, on the prompts that were taking the longest before, they’re now just, like, reduced by, like, 90% due to, like, the migration.
221 00:24:27.900 ⇒ 00:24:28.400 YvetteRuiz: 10.
222 00:24:28.580 ⇒ 00:24:44.759 Pranav: now, after this week, when we have, like, the new, restructure central docs, as well into this, you know, into the new Andy, we’ll do, like, a more end-to-end, like, total… like, we’ll track basically, like, all the different prompts that were asked.
223 00:24:44.760 ⇒ 00:24:49.630 Pranav: In the, in the… like, historically into ND, and then we’ll just give you some better numbers there.
224 00:24:50.130 ⇒ 00:25:05.750 YvetteRuiz: Okay, all right, and so, you know, because I was talking to Steven and Matt yesterday before, I mean, last week before I went on my PTO time, because I was just kind of giving them an update after our conversation for now. So originally, you know, when we met with Utam.
225 00:25:05.750 ⇒ 00:25:15.650 YvetteRuiz: And so, gosh, this is Scott. You know, we talked about it being between 2 and 3 seconds. Do we feel like we would be able to get the response time to
226 00:25:15.670 ⇒ 00:25:18.299 YvetteRuiz: You know, the 2-3 second mark?
227 00:25:18.950 ⇒ 00:25:31.020 Pranav: So, we’re doing some updates right now with, Casey to, like, further get the execution time down. Right now, what we’re seeing on average is 5-ish seconds. Okay.
228 00:25:31.020 ⇒ 00:25:32.410 YvetteRuiz: Oh, wow, okay.
229 00:25:32.710 ⇒ 00:25:40.590 Pranav: Which is much better, and I want to do, like, the full testing before I give you, like, concrete numbers, and we’ll have all of that in real as well.
230 00:25:41.380 ⇒ 00:25:46.940 Pranav: we’ve made, like, a huge jump, right? Like, basically, that’s what I’m seeing.
231 00:25:48.720 ⇒ 00:25:56.719 Pranav: Let’s, like, look at that data first. Let’s look at, like, what the exact execution time is, because I don’t want to say a number that isn’t true.
232 00:25:56.730 ⇒ 00:26:05.819 Pranav: But… and this week, too, we’ll be finalizing all of the improvements that we’ve been talking about for the last, last few weeks that I’ve been here, right? So,
233 00:26:05.820 ⇒ 00:26:17.470 Pranav: once we get that number out, we’ll talk about, like, okay, how does this look? Do we need to… we have additional… there’s always some additional tweaks that we can do to kind of further, further refine this.
234 00:26:17.500 ⇒ 00:26:28.750 Pranav: I just want to do whatever’s, like, the most pressing for y’all, right? Like, what’s gonna be the biggest value gain? If it is really getting, like, an extra second, then we can talk about that, we can talk about why.
235 00:26:28.870 ⇒ 00:26:38.019 Pranav: And we’ll talk about, like, what that means, like, what we have to do on our end to get there. But let’s first, like, get that report out to you guys, which will be…
236 00:26:38.180 ⇒ 00:26:52.559 Pranav: Either end of this week or, like, sometime next week. End of this week, we’ll have all of the, you know, we’ll finish all of our dev work, we’ll do some QA, but then creating that actual report may be, like, Monday or Tuesday of next week.
237 00:26:52.920 ⇒ 00:27:07.049 YvetteRuiz: Okay, that’ll be perfect. Just so you guys know, we’re changing a little bit of the way we’re doing our QA monitoring, so we have a… well, Amber, you know, CallSource does all our… well, not every single call, but
238 00:27:07.050 ⇒ 00:27:16.640 YvetteRuiz: a big chunk of the monitorings of our phone calls for score grading. And then, of course, the coaching’s done by our QA manager.
239 00:27:16.640 ⇒ 00:27:40.270 YvetteRuiz: we’re… I… we’re changing up the way she’s doing it, and she’s going to be doing more sit-alongs with real time to be able to listen in at real time, and one of the things that I’ve tasked her with when she’s part of the scorecard is, are they using the Andy wash while they’re on the phone calls as well? Because then I want her to be able to provide me, information as well when she’s sitting, you know, there with them as…
240 00:27:40.510 ⇒ 00:27:43.469 YvetteRuiz: you know, feedback, and so one of those things I know
241 00:27:43.660 ⇒ 00:27:46.360 YvetteRuiz: If we can get the execution time down.
242 00:27:46.470 ⇒ 00:27:53.190 YvetteRuiz: that is going to be super helpful, because I know that I’ve done a couple of sit-alongs with some of our CSRs, and that was kind of a little bit of a…
243 00:27:53.740 ⇒ 00:27:55.529 YvetteRuiz: a delay.
244 00:27:56.270 ⇒ 00:27:57.470 Pranav: That makes sense.
245 00:27:58.600 ⇒ 00:28:01.709 YvetteRuiz: But… Thank you for that.
246 00:28:01.980 ⇒ 00:28:02.650 Pranav: Totally.
247 00:28:04.950 ⇒ 00:28:29.929 YvetteRuiz: All right. I mean, it looks like a lot of good stuff. We’re making a lot of positive moves, but thank you very much for your help. You know, the Central Doc stuff looks fairly clean, very good, and again, you saw my email to the teams to make sure that they’ve had the time to review it and come to the table with their feedback, and, so hopefully we’ll have a good meeting, from that. And then, like I said, those meetings will be put on a pause because
248 00:28:29.930 ⇒ 00:28:45.500 YvetteRuiz: I feel like now that Janiece is working with them one-on-one, you know, we’re going to start seeing more and more progress, I feel. And then being able to add the dashboard and a little bit more KPIs to kind of really tie into that, I think that’s even going to be even more impactful.
249 00:28:45.910 ⇒ 00:29:02.340 Pranav: Awesome. Yeah, and Janice, we can probably schedule one-on-ones for just me and you, or just have them ad hoc, just based on, like, your conversations that you have with them. Feel free to just, like, whenever you have, like, you find something with a trainer, just to, like, message that to me, like, within the Google Chat, and then…
250 00:29:02.410 ⇒ 00:29:06.040 Pranav: I will then, like, track these and figure out what we can do on our end.
251 00:29:07.220 ⇒ 00:29:13.029 JanieceGarcia: With the Google Chat, do you… am I using yours directly that you had.
252 00:29:13.030 ⇒ 00:29:13.420 Pranav: Yeah.
253 00:29:13.420 ⇒ 00:29:16.020 JanieceGarcia: for us, or do you… with the Brain Forge one?
254 00:29:16.420 ⇒ 00:29:21.439 Pranav: I think if you don’t mind doing it to me directly, it’s just much easier for me to, like, respond quicker.
255 00:29:21.810 ⇒ 00:29:23.629 JanieceGarcia: Okay, okay, will do.
256 00:29:23.810 ⇒ 00:29:24.839 Pranav: Appreciate that, yeah.
257 00:29:25.920 ⇒ 00:29:26.650 Pranav: Alright.
258 00:29:27.580 ⇒ 00:29:29.970 Pranav: So we have that meeting tomorrow, we’ll talk then.
259 00:29:30.550 ⇒ 00:29:31.130 JanieceGarcia: Okay.
260 00:29:31.350 ⇒ 00:29:32.650 YvetteRuiz: Alright, thanks, mine!
261 00:29:32.650 ⇒ 00:29:33.470 JanieceGarcia: Q.
262 00:29:33.470 ⇒ 00:29:35.149 YvetteRuiz: Alright, have a good one. Bye.
263 00:29:35.820 ⇒ 00:29:36.570 Pranav: See ya.